MANAGING DATA REPLICATION IN MOBILE AD- HOC NETWORK DATABASES (Invited Paper) *

Transcription

1 MANAGING DATA REPLICATION IN MOBILE AD- HOC NETWORK DATABASES (Invited Paper) * Praanna Padmanabhan School of Computer Science The Univerity of Oklahoma Norman OK, USA praannap@yahoo-inc.com Dr. Le Gruenwald School of Computer Science The Univerity of Oklahoma Norman, OK, USA ggruenwald@ou.edu Abtract A Mobile Ad-hoc Network (MANET) i a collection of wirele autonomou node without any fixed backbone infratructure. All the node in MANET are mobile and power retricted and thu, diconnection and network partitioning occur frequently. In addition, many MANET databae tranaction have time contraint. In thi paper, a Data REplication technique for real-time Ad-hoc Mobile databae () i propoed that addree all thoe iue. It improve data acceibility while conidering the iue of energy limitation by replicating hot data item at erver that have higher remaining power. It addree diconnection and network partitioning by introducing new data and tranaction type and by conidering the tability of wirele link. It handle the real-time tranaction iue by replicating data item that are acceed frequently by firm tranaction before thoe acceed frequently by oft tranaction. i prototyped on laptop and PDA and compared with two exiting replication technique uing a military databae application. The reult how that perform the bet in term of percentage of uccefully executed tranaction, erver and client energy conumption, and balance of energy conumption ditribution among erver. I. INTRODUCTION MANET i a collection of wirele autonomou node that may move unpredictably, forming a temporary network without any fixed backbone infratructure [4]. All the node in MANET are mobile and, thu, retricted by power. Thee node not only can communicate with node that are within their communication range, but alo can communicate with node that are outide their tranmiion range uing multi hop communication. Since no fixed infratructure i required, they fit well in military, recue operation and enor network [8]. Moreover many application in thi environment are timecritical and, hence, their tranaction hould be executed not only correctly, but alo within their deadline. In a ditributed databae ytem, data are often replicated to improve reliability and availability. However one important iue to be conidered while replicating data i the correctne of the replicated data. Since node in MANET are mobile and have limited energy, diconnection may occur frequently, cauing a lot of network partitioning. Data that i available in mobile hot in one partition cannot be acceed by mobile hot in another partition. The iue related to data replication in MANET databae are a follow: Server Power Conumption: Server in MANET run on battery power. If a erver ha low power remaining and if it i replicated with many frequently acceed data item, then the frequent data acce requet for thee hot data will drain it power. Server mobility: Due to their mobility, erver might ometime move to a place where they could not be reached by any other erver or client. Client mobility: Client that query erver for information are alo mobile. Client uually end their tranaction to the nearet erver to get a quick repone. The deciion to replicate data item at a particular erver may be baed on the acce frequencie of data item from that pecific erver. Hence, the deciion to replicate data item at appropriate erver mut be dynamic and baed on the current network topology. Client Power: Client in MANET alo run on battery power. If a client wait too long for it tranaction reult, it might loe it power rapidly. The replication technique hould be able to replicate data * Thi work wa upported in part (while erving at) by the National Science Foundation (NSF) and NSF Grant No. IIS /6/$2. 26 IEEE

2 item at appropriate erver in uch a way that a client might be able to acce it requeted data item from it nearet erver which ha the leat workload. Time-critical application: Many MANET application, like recue network, military operation, are time-critical. Data replication hould be ued to improve data acceibility and performance of the ytem, thereby reducing the time to execute tranaction. Tranaction with hort deadline hould be ent to the nearet erver that have the leat workload for their execution. Thee tranaction hould alo be executed before other tranaction that have longer deadline. Frequent Diconnection and Network Partitioning: Diconnection and network partitioning i a evere problem in MANET a erver in one partition that hold required data item cannot provide ervice to other client and erver in different partition. Update tranaction: If there are no contraint in torage pace and if there are read-only tranaction, data acceibility and performance of MANET databae can be increaed by fully replicating the databae in all the erver. However, maintaining conitency in a fully replicated databae i a major iue when there are frequent update tranaction. No ingle exiting replication technique conider all of the above iue. In the poter paper [17b], we have briefly preented a replication technique, called that addree all the above iue. In thi paper, we dicu thi technique and it performance evaluation in detail. The ret of the paper i organized a follow. Section 2 review the related work. Section 3 decribe the underlying MANET databae ytem architecture. Section 4, 5 and 6 preent, the prototype model and the performance evaluation reult, repectively. Finally, Section 7 conclude the paper with future work. II. RELATED WORKS A data replication technique that replicate data item baed on their acce frequencie and the current network topology i propoed in [6]. Hot data are replicated before cold data item. If the acce characteritic of data item are imilar, there could be replica duplication at many mobile node. Hence, two other technique to reduce replica duplication between mobile node are propoed in [6]. They alo detect network partitioning and replicate hot data item before uch a partitioning occur to improve data acceibility. However in thoe technique, when there i a replica duplication between any two connected mobile node, one of the duplicate replica i replaced by another hot data item, irrepective of how high the acce frequency of the replaced data item i or how low the acce frequency of the new data item i. A data replication technique that replicate data item at multiple node and employ quorum baed trategie to update and query information i propoed in [11]. It end the update information to node in uch a way that other node while querying for thi update information get the mot updated information, and thereby, reducing inconitency and dirty read tranaction. It determine the time to end the update, where to end them and which node to query for the information in uch a way that it mitigate the impact of network partitioning. Another way of dieminating the update information to mobile node i by data broadcating a propoed in [19]. Thi replication technique delay the update to replica for performance and bandwidth conideration. It alo determine what update to broadcat and when to broadcat them in an efficient manner. A et of protocol that ue a goip-baed multicat protocol to probabilitically dieminate update in a quorum ytem i propoed in [15]. It achieve high reliability even when there are large concurrent update and query tranaction. A new metric for evaluating wirele link robutne that i ued to detect network partitioning i propoed in [7]. It deciion to replicate data item i taken not only at the time of detecting network partitioning, but alo during the time when the wirele connection become bad in term of reliability, bandwidth and delay. Roam [18] i a replication technique that attempt to provide data availability to mobile hot irrepective of the mobility of the hot. It model the mobility of hot by grouping them into ward and determine period of motion of the mobile hot. Ward mater are elected to provide communication acro ward, but hot belonging to the ame ward may directly communicate with each other. Roam maintain conitency of replica acro the network, irrepective of the location of movement different hot. None of the above replication technique addree the iue related to real-time databae tranaction and mobile hot power limitation. It hould alo be noted that network partitioning might occur not only due to mobile hot mobility, but alo due to battery power drainage of ome mobile hot. Client1 III. DECENTRALIZED MANET DATABASE ARCHITECTURE Server1 Server2 Server3 Client3 Client2 Client26 Figure 1: Decentralized MANET Databae Architecture

3 Depending on communication trength, computing power, dik and memory torage ize, mobile hot can be claified into two group: Client and Server. Client are equipped with reduced memory and computing capabilitie. They tore only the Query Proceing module of the Databae Management Sytem (DBMS) that allow them to ubmit tranaction to appropriate erver and receive reult. Server are equipped with higher memory and computing capabilitie; they tore the complete DBMS. For example, oldier in battlefield, who are equipped with handy portable computer like PDA and mart phone, could be conidered a client, while tank and humvee equipped with high end portable computer like laptop could be conidered a erver. Thi paper aume a decentralized architecture, where client are free to communicate (ingle-hop or multi-hop) and ubmit their tranaction to any of the available erver in the network a hown in Figure 1. Thi architecture doe not place reliance on any centralized erver and, thu, improve ytem reilience by avoiding a ingle point of failure. IV. PROPOSED MANET DATA REPLICATION TECHNIQUE: A data replication for MANET databae, called, i propoed in thi ection. It extend the technique propoed in [6] that have briefly been reviewed in Section 2 to conider additional iue including mobile hot power limitation, real-time databae tranaction a well a variou data and tranaction type that exit in many MANET application. improve data acceibility while addreing the iue of power limitation by replicating hot data item before cold data item at erver that have high remaining power. It handle the real-time tranaction iue by giving a higher priority for replicating data item that are acceed frequently by firm tranaction than thoe acceed frequently by oft tranaction It addree diconnection and network partitioning by introducing new data and tranaction type and by determining the tability of wirele link connecting erver. The remaining energy of connecting erver i alo ued to meaure their link tability. The data and tranaction type are propoed in Section A and B, repectively, after gathering the databae requirement of a fire recue and a battlefield application from the Norman Fire Department and the Reerve Officer Training Corp (ROTC) at the Univerity of Oklahoma. Each erver in that hold the original copy of a data item i termed it primary copy erver and the other erver that hold the replica of the data item are termed it econdary copy erver. addree the replica ynchronization iue by maintaining two timetamp that indicate when a particular data item i updated in it primary and econdary copy erver. i compoed of three main part. The firt part determine the data item to be replicated and the erver in which they have to be replicated. The econd part determine how the allocated replica can be acceed for tranaction proceing baed on their data and tranaction type. The third part identifie the way to ynchronize the replica. Thee part are dicued in ubequent ection. A. Data Type data type are hown in Figure 2. Data item are claified into read-only and read-write data item. Read-write data item can be further claified into two type: Temporal and Peritent. The former are thoe data item the value of which are valid only for a certain period of time. The location of a oldier and the location of an enemy are example of temporal data item a they move frequently in a battlefield. However, peritent data item are valid throughout their exitence in the databae. Location of medical aitance and a lit of wounded oldier are example of peritent data item. All read-write data item can be further claified into periodic and aperiodic update data item. Periodic update data item are thoe data item that are updated periodically at fixed interval of time. For example, the location of a oldier may be updated frequently at a contant interval of time. Aperiodic-update data item are thoe data item that are updated at random interval of time. For example, the location and information about an enemy may be updated at random time interval. Temporal Data Item Periodic Update Aperiodic Update Figure 2: Data Type B. Tranaction Type The tranaction type propoed in are hown in Figure 3. Tranaction, both firm and oft, are claified a read and write tranaction. Read Tranaction Data Item Read- Only Data Item Tranaction Periodic Update Write Tranaction Overwrite Current MR MRVP Outdated Inert/ Delete Value MRV Mot Recent Value Tranaction MRVP Mot Recent Value in a Partition Figure 3: Tranaction Type Peritent Data Item Aperiodic Update Ue Current Value Read tranaction: they are further claified into three ub-categorie depending on the frehne of the data

4 read. Some tranaction need the mot recent value of data item acro all the databae erver in the network for tranaction proceing. Thee tranaction are called Mot Recent Value (MRV) tranaction. For example, a military officer might need the mot recent location of an enemy to launch a miile. Some other tranaction give le importance to the frehne of the data for tranaction proceing and can be executed even if the retrieved data i tale. Such tranaction are called outdated tranaction (OD). For example, a oldier might need the weather information of a particular place to prepare for hi or her clothing. Another type of read tranaction i called the Mot Recent Value in a Partition (MRVP) tranaction. Thee tranaction require the mot recent value of data item acro all the databae erver in a network partition. The reult of a MRVP tranaction may or may not be the mot recent value of the requeted data item acro the entire databae. For example, a wounded oldier might query for the location of medical aitance. Thi tranaction would have ideally been a MRV tranaction. However in a MANET environment, not all node are connected all the time and, hence, the mot recent value of data item acro all the databae erver may not ometime be determined. An outdated tranaction for thi cae i alo not an ideal one. Therefore, the mot recent value of the required data item acro all the databae erver in the network partition in which the wounded oldier currently reide hould be returned back to him or her. Write tranaction: they are further divided into three ub-categorie depending on how their data update occur. Some write tranaction inert or delete record into the databae. Thee tranaction are called Inert/Delete tranaction. Another type of write tranaction i called the Ue Current Value (UCV) tranaction. Thee tranaction need the current value of data item for tranaction proceing. For example in a military application, a oldier might update the number of wounded oldier by a certain value. For thi tranaction to be uccefully executed, the number of currently wounded oldier mut be known. Another type of write tranaction i called the Overwrite Current Value (OCV) tranaction. Thee tranaction overwrite the current value of data item and can be executed uccefully irrepective of the current value of the data item. For example, oldier in a battlefield may update their location periodically and uch update operation on their location overwrite the current value of their location. C. What and Where to Replicate? Figure 4 how thi part of. Each erver in can tore only a certain number of data item, called maximum capacity. The firt tep of the algorithm i to calculate the weighted acce frequencie of data item baed on their data and tranaction type. After determining their weighted acce frequencie, data item with higher weighted acce frequencie (hot data item) are replicated before data item with lower weighted acce frequencie (cold data item) in erver that have the maximum remaining power. After toring the hot data item at appropriate erver, if there are any redundant data item among neighboring erver, they are eliminated depending upon the tability of the link connecting them and the acce frequencie of the next available hot data item. Such a deciion to replicate data item at appropriate erver i taken every time during a certain period of time called the relocation period [6]. 1. Computing Acce Frequencie baed on Data and Tranaction Type Acce frequency of a data item d at a particular erver, Acce_Frequency d, i the number of time that d i acceed at. From the acce log, imilar to [6], the acce frequency of each data item at each erver i computed. In addition, in, the number of time a data item i acceed by Firm, Soft, MRV and Non- UCV tranaction at all erver are computed. Thee are computed only once by all the erver when running the replication algorithm for the firt time. Thee acce frequencie are then further calculated uing a weight factor baed on the data and tranaction type preented in Section 4.1 and 4.2. The reulting acce frequencie are thu the weighted one to reflect replication prioritization a hown in the following ection. a) Firm and Soft Tranaction: if a data item i acceed more often by firm tranaction than another data item i, then the former data item i given a higher priority to be replicated than the latter. Thi i to reduce the number of tranaction abort ince firm tranaction mut be aborted if they mied their deadline. Firm tranaction execution time can decreae coniderably if their required data item reide in the erver to which the requet were ent. The replication priority i et by aigning weighted acce frequencie to data item that are acceed by firm tranaction uing the below formula where Acce_Frequency d_firm i the number of time data item d i acceed by firm tranaction at erver. Acce_Frequency d = Acce_Frequency d + Acce_Frequency d_firm * (Acce_Frequency d_firm / Acce_Frequency d ) b) Temporal Data Item: a temporal data item i valid only for a certain time period called it age. If the time remaining during which a temporal data item i valid i greater than the relocation period, then the probability for uccefully acceing that temporal data item until the next relocation period i high a the temporal data item i valid throughout the entire relocation period. However, if the remaining valid time interval i le than the relocation period, then the temporal data item i valid for

5 only ome portion of the relocation period. The ratio between the remaining valid time interval and the relocation period i called the Age Relocation Ratio of a temporal data item. A data item with a higher age relocation ratio i replicated before the one with a lower age relocation ratio. Thi i becaue the probability of uccefully executing a tranaction that accee the former i more than the one acceing the latter a the former i valid for a longer interval of time. Hence, the weighted acce frequency of a temporal data item i calculated baed on it age relocation ratio uing the following formula where Age_Relocation_Ratio d i the Age Relocation Ratio of temporal data item d at erver. Acce_Frequency d = Acce_Frequency d * Age_Relocation_Ratio d c) Read-Write Data Item: a read-write data item that i acceed frequently by UCV tranaction i given a lower priority to be replicated than a read-write data item, which ha the ame acce frequency a the former and i acceed frequently by Non-UCV tranaction. Thi i due to the fact that the probability of executing an UCV tranaction i lower than the probability of executing a Non-UCV tranaction a the latter can be executed irrepective of the current value of their required data item. Similarly, the probability of uccefully executing a MRV tranaction i lower than the probability of uccefully executing a Non-MRV tranaction. Thu, a read-write data item that i acceed frequently by MRV tranaction i given a lower priority to be replicated than a read-write data item which ha the ame acce frequency a the former and i acceed frequently by Non-MRV tranaction. 2. Replica Allocation and Redundancy Elimination By comparing the movement of two connected neighboring erver, the ditance between them can be calculated. Baed on their ditance, tranmiion range and velocity, the time in which they would be diconnected can be etimated a preented in [6]. Thi time i called the diconnection time of thee two erver. If the diconnection time of two erver i greater than the relocation time period, thee two erver can hare data reliably until the next relocation time period. However, unlike [6] which doe not addre mobile hot power limitation, we believe that even if two erver are within each other tranmiion range, they might not be able to communicate with each other if they are out of power. Hence, in, the link tability connecting two erver until the next relocation period i given by the formula: Reliability Ratio = Percentage of Server Power Remaining * (diconnection time / relocation period) A higher reliability ratio between two erver mean that the link connecting them i more table to hare data between them. For example, if the reliability ratio of two erver i.5, then only for 5% of the relocation period can thee erver hare data, while for the ret of the time they might be diconnected. After determining the acce frequencie and the reliability ratio of all erver, data item in the decending order of their acce frequencie are aigned to erver until the max capacity of data item in thoe erver ha been reached. If the acce frequencie of data item are imilar at many erver, the ame data item would be replicated at thoe erver [6]. Replica duplication among neighboring erver can be eliminated by replacing a duplicate data item with the next highet acceed data item a preented in [6]. However, if thoe neighboring erver get diconnected in the future, data acceibility would even decreae becaue of uch a replacement. Hence, in, the deciion to eliminate redundancy i taken only if it improve data acceibility. Aume there i a replica duplication of a data item d x between two neighboring erver, i and j. The deciion to remove thi redundancy in i baed on the following two condition: a) One of the erver (ay i ) i the primary copy erver of d x : in thi cae, the next highet acceed data item in j, d y, i computed. Thi data item d y can replace d x in j only if the link connecting i and j i table o that all requet for d x in j can be uccefully executed by forwarding the requet to i. There i, however, no ue in replacing d x by d y if the difference between the acce frequencie of d x and d y in j i very high or if the link connecting i and j i unreliable. A dicued above, the reliability ratio of two erver indicate the tability of the link connecting them. It i beneficial to replace d x by d y in j only if the um of the number of time that d y can be acceed from j (Acce_Frequency j dy ) and the number of time that d x j can be acceed from i (Reliability_Ratio i * Acce_Frequency j dx ) i greater than the number of time that d x can be acceed from j (Acce_Frequency j dx ). b) Both of the erver are econdary copy erver of d x : when thee erver, i and j, hold only the replica and not the original copy of d x, the deciion to remove thi redundancy i baed on the acce frequencie of the next frequently acceed data item in both i and j. The next frequently acceed data item, d u and d v, for i and j, repectively, are computed. A in cae (a), firt determine if it i beneficial to replace d x by d u in i, and d x by d v in j. If either of one of them i beneficial, then d x i replaced by the appropriate data item at the erver in which it i beneficial. If none of them i beneficial, then the redundancy i not eliminated. If both of them are beneficial, the redundancy i eliminated in the erver in which more benefit i obtained.

6 What_to_Replicate_in_Which_Server(data_item d, erver, data_type, Acce_Frequency d, Relocation_Period) /* Valid_Remaining_Time d the time remaining until which the temporal data item d in the erver i valid; Abolute_Validity_Interval d the abolute validity interval of data item d in erver ; Timetamp_Current_Value d the time when the current value of the temporal data item d i obtained in erver */ Begin /* Compute the acce frequencie of data item baed on their data type */ If (d i a Temporal Data Item) Compute Valid_Remaining_Time d uing the formula Valid_Remaining_Time d = Timetamp_Current_Value d + Abolute_Valid_Interval d T now If (Valid_Remaining_Time d >= Relocation_Period) Age_Relocation_Ratio d = 1 Ele Age_Relocation_Ratio d = Valid_Remaining_Time d / Relocation_Period /* Acce frequencie of temporal data item are computed baed on their remaining valid time period */ Acce_Frequency d = Acce_Frequency d * Age_Relocation_Ratio d If (d i a read-write data item) If ( i not the primary copy erver of d) /* aume p i the primary copy erver of d UCV and MRV tranaction acceing d hould be forwarded to p */ Acce_Frequency d =Acce_Frequency d_non UCV + Acce_Frequency d_non MRV + Reliability_Ratio p * (Acce_Frequency d_ucv + Acce_Frequency d_mrv ) Store maxcapacity number of data item in decending order of their acce frequencie in erver For each erver i For each erver j adjacent to i For all data item d x that i redundant between i and j If (one i a primary copy erver (ay i ) and the other a econdary copy (ay j )) Find the next highet acce frequency data item, d y, in j /* Replace d x by d y in j only if the um of the number of time that d y can be acceed from j (Acce_Frequency j dy ) and the number of time that d x can be acceed from i (Reliability_Ratio j i * Acce_Frequency j dx ) i greater than the number of time that d x can be acceed from Acce_Frequency j dx ); d x hould be replaced by d y in j only if it would increae data acceibility */ If (Acce_Frequency j j dy + Reliability_Ratio i * Acce_Frequency j dx > Acce_Frequency j dx ) Replace d x by d y in j Ele if (Both i and j are econdary copy erver) /* either change one or change none */ Find the next highet acce frequency data item d u and d v for i and j,, repectively. /* Can_d u _Replace_d x Check if the data acceibility would be improved if d x i replaced by d u in i. Thi i done by checking if the um of the number of time that d u can be acceed from i (Acce_Frequency du i ) and the number of time that d x can be acceed from j (Reliability_Ratio j i * Acce_Frequency dx i ) i greater than the number of time that d x can be acceed from i (Acce_Frequency dx i ) */ Can_d u _Replace_d x = Acce_Frequency du i + Reliability_Ratio j i * Acce_Frequency dx i > Acce_Frequency dx i /* Can_d v _Replace_d x Check if the data acceibility would be improved if d x i replaced by d v in j. */ Can_d v _Replace_d x = Acce_Frequency dv j + Reliability_Ratio i j * Acce_Frequency dx j > Acce_Frequency dx j If (Not Can_d u _Replace_d x && Not Can_d v _Replace_d x ) The redundancy i not eliminated in either of the erver Ele If (Can_d u _Replace_d x && Can_d v _Replace_d x ) /* If the data acceibility i more when d x i replaced by d u in i than when d x i replaced by d v in j, then d x will be replaced by d u in i ; ele d x will be replaced by d v in j */ If (Acce_Frequency i i dv + Reliability_Ratio j * i Acce_Frequency dx > Acce_Frequency j dv + Reliability_Ratio j i * Acce_Frequency j dx ) Replace d x by d u in i Ele Replace d x by d v in j Ele If (Can_d u _Replace_d x ) Replace d x by d u in i Ele Replace d x by d v in j End For End For End For End What_to_Replicate_in_Which_Server Figure 4: What and Where to Replicate in D. How to Acce Replica? Due to pace limitation, we preent here only the baic idea of the algorithm; intereted reader are referred to [17] for the detailed algorithm. Once data item are replicated at appropriate erver, they are acceed in different way baed on the propoed data and tranaction type. When there i a requet for a data item d to a erver that i the primary copy erver of d, d can be acceed directly from that erver, irrepective of it data type. If the initiated tranaction i a write

7 tranaction, the primary copy erver, after updating it original copy of d, broadcat it update timetamp to indicate to the other econdary copy (replica) erver that hold d that their replica are out of ynchronization. In contrat, if the coordinating erver i not the primary copy erver of the requeted data item, the data item i acceed in different way baed on the data and tranaction type a dicued in the following ection. Every erver that hold a replica of data item d ha two timetamp: the time when d i updated in, Local_Update_Timetamp d, and the time when d i updated at it primary copy erver, Primary_Update_Timetamp d. Thee two timetamp are ued to determine if the replica i in ynchronization with the original copy. 1. Read Tranaction If the requeted data item i a read-only data item, it can be acceed from any erver that hold it. Similarly, if the initiated tranaction i an OD tranaction, it can be acceed from any erver that hold it. For both of thee two cae, if the requeted data item i available at more than one erver, the deciion to chooe an appropriate erver i baed on the real time tranaction type. A firm tranaction i ent to the nearet erver with the leat workload, while a oft tranaction i ent to the highet energy erver with the leat workload, for tranaction proceing. The objective i to reduce the number of tranaction abort and, at the ame time, balance the energy conumption ditribution among erver. If the requeted tranaction i a MRV tranaction, the requeted data item hould be acceed from the erver that ha it mot recent value among all the erver that hold it. If the requeted tranaction i a MRVP tranaction, the requeted data item hould be acceed from the erver that ha it mot recent value among all the erver in it network partition that hold it. Baed on the Local_Update_Timetamp d of all erver, the mot recent value of data item d can be determined. A periodic update data item i updated once every certain period of time called it update frequency. Hence, a MRV or a MRVP tranaction acceing a periodic update data item can acce it from any erver that ha updated it during it lat known update time interval. For example, conider a periodic data item d that i updated every one hour. A erver ha the mot recent value of d if the difference between the current time (T now ) and the lat update timetamp of d in (Local_Update_Timetamp d ) i le than it update frequency (Frequency_Update d ), which i one hour in thi example. 2. Write Tranaction If the tranaction i an update tranaction and if the coordinating erver i connected to the primary copy erver of the requeted data item, the update tranaction i forwarded to the primary copy erver for tranaction proceing. If the coordinating erver hold a replica of the requeted data item, and if the tranaction i not an UCV tranaction, the local replica i alo updated a further read requet for that data item can be acceed directly from the local replica. However, if the coordinating erver i not connected to the primary copy erver, and if the tranaction i not an UCV tranaction, the update tranaction i forwarded to the erver that hold the requeted data item. If there i more than one erver that hold the requeted data item, a firm tranaction i ent to the nearet erver that ha the leat workload and a oft tranaction i ent to the highet energy erver that ha the leat workload for tranaction proceing. However, if the tranaction i an UCV tranaction, we need the mot recent current value of the requeted data item for tranaction proceing. The mot recent current value of a data item uually reide at it primary copy erver. However, if the coordinating erver i not connected to the primary copy erver a in thi cae, the tranaction cannot be executed uccefully. Hence, the coordinating erver will try to connect to the primary copy erver unle the deadline of thi tranaction ha expired, in which cae the tranaction i aborted. The deadline here mean the firt deadline if the tranaction i firm and the econd deadline if the tranaction i oft. E. How to Synchronize Replica? Every time during the relocation period, the primary copy erver of a data item trie to ynchronize it data item with other connected erver that hold it replica. The primary copy erver requet for the lat updated timetamp from all replica. Baed on the update timetamp of the primary copy and the update timetamp of the replica, the primary copy erver determine if there i any other erver that ha a more recent value of it data item. If uch a erver exit, the new value of the data item i ynchronized with all other erver. However, a erver that i diconnected from the network during the relocation period cannot ynchronize it data item. Even if the diconnected erver ha the mot recent value of the data item, the primary copy erver cannot determine it ince the former i diconnected. Hence, it will only try to ynchronize the data item during the next relocation period. V. PERFORMANCE EVALUATION - PROTOTYPE MODEL After conidering the variou open ource databae erver and client baed on our application requirement, we have choen MySQL [16] erver on Linux a the framework for our erver databae and DALP (Databae Acce Librarie for PDA) [2] on Window CE a the framework for our client databae ytem. We have modified the OLSR routing protocol in Linux to route packet and broadcat additional information like the energy and poition of each mobile hot. We have ued a

8 Global Poitioning Sytem (GPS) to track the location of mobile hot that are ued for both routing packet and for Table I: Static Parameter Parameter Value Memory_Size_Server 512 MB [3] Memory_Size_Client 127 MB [] Proceor_Speed_Server 2.8 GHz, 553 MIPS [3] Proceor_Speed_Client 2MHz, 35 MIPS [] Battery_Life_Server 3hr [3] Battery_Life_Client 2.5hr [] Bandwidth_Server 11 Mbp [14] Bandwidth_Client 11 Mbp [1] Table II: Dynamic Parameter Default Parameter Range value IAT (Inter Arrival Time between tranaction) Firm Tranaction Probability MRV Tranaction Probability MRVP Tranaction Probability OD Tranaction Probability Temporal Data Probability Number of Partition MH diconnection probability Broadcat Frequency.5 Expon (.1 1) [13].5,.25,.5,.75, 1.34,.25,.5,.75, 1.33,.25,.5,.75, 1.33,.25,.5,.75, 1.4,.25,.5,.75, 1 2 1, 2, 3.5 PROB(.1) TO PROB(.9) [13] 2 ec 2- ec Relocation Time 256 ec ec [5] Acce Frequency Characteritic (p i ) Periodic Update Frequency.5 Zip parameter -.99 [9] ec ec [6] efficient tranaction proceing. We have modified MySQL and DALP to include our algorithm,. We have ued thi prototype to compare with the replication technique propoed in ([5], [6]), which we call the model and the baeline model. Section 5.1 and 5.2 decribe the client and the erver tranaction workflow in our prototype, repectively, and Section 5.3 decribe the tet databae application. The deadline of a tranaction i computed baed on it run time etimate and lack factor. A oft tranaction econd deadline i twice a that of it firt deadline. The performance i meaured in term of the percentage of tranaction uccefully executed, energy conumption of erver and client, and the average difference in energy conumption between two erver. Thi third metric meaure the balance of energy conumption ditribution among erver. The tatic and the dynamic parameter ued in our prototype model are hown in Table 1 and 2, repectively. The impact of the following five dynamic parameter are reported in thi paper: firm/oft tranaction ratio, tranaction inter-arrival time, probability of mobile hot diconnection, number of network partition and broadcat interval. A. Client Side Each client i provided with an eay to ue interface to generate real time tranaction and aociate appropriate deadline to them. DALP provide a et of application programming interface that allow handheld device to connect to MySQL databae. The client end it firm tranaction to the nearet erver that ha the leat workload for proceing to minimize the chance of miing their deadline, while it end it oft tranaction to the highet energy erver that ha the leat workload for profeing o that a balance of energy conumption of mobile node can be achieved. When the tranaction execution i completed, the client receive the tranaction reult and diplay them to the end uer. B. Server Side The databae erver after receiving a tranaction fdetermine if it i a global tranaction uing it global conceptual chema. Ditributed tranaction proceor functionality ha been added to the MySQL databae erver, which divide tranaction into ub-tranaction and forward thee ub-tranaction to appropriate participating erver() that hold the required data. The local tranaction proceor then forward thee tranaction to the real time cheduler that we have built into the MySQL erver. The real time cheduler chedule tranaction with horter deadline for execution before thoe with longer deadline. The MySQL erver ha alo modified to include a commit protocol that decide to abort or commit the tranaction after communicating with the participating erver. After executing the commit protocol, the MySQL erver end the reult back to the client. C. Tet Databae Application We have obtained the data and tranaction requirement for a military databae application from the Reerve Officer Training Corp (ROTC) at the Univerity of Oklahoma. We have created relational databae table for thi application, populated each table with one million row of data, and generated tranaction to retrieve and update the data in the table.

9 VI. PERFORMANCE EVALUATION RESULTS from erver i much le than the gain it make in term of the number of tranaction uccefully executed. A. Impact of Firm/Soft Tranaction Ratio The impact of the firm/oft tranaction ratio on the percentage of uccefully executed tranaction and the erver energy conumption i hown in Figure 6. More tranaction mi their deadline a the ratio of firm to oft tranaction increae. Tranaction with longer deadline have more time to be proceed and, hence, the probability of uccefully executing uch tranaction i high. give more priority for data item that are acceed frequently by firm tranaction than thoe that are acceed frequently by oft tranaction. Hence, ha more uccefully executed tranaction. Conequently, the power conumption of erver in i the highet. However, the difference in erver energy conumption between and the other two model i coniderably lower compared to the difference in the number of uccefully executed tranaction. Percentage of Succefully Executed Tranaction Average Server Energy Conumption Percentage Tranaction Inter-Arrival Time Tranaction Inter-Arrival Time Percentage of Succefully Executed Tranaction Average Server Energy Conumption Percentage Percentage of Firm Tranaction Percentage of Firm Tranaction Figure 6: Impact of Firm/Soft Tranaction Ratio B. Impact of Tranaction Inter-Arrival Time In thi experiment, the effect of ytem workload i tudied by varying the tranaction inter-arrival time. A tranaction inter-arrival time increae, the peed of generating tranaction decreae and, hence, the ytem workload decreae. Thu, tranaction have le waiting time for reource and, ubequently, have a higher probability for ucceful execution. Since uccefully execute more tranaction, the power conumption of erver in thi model i more than that in the other two model. However, Figure 7 alo how that the additional amount of energy that require Figure 7: Impact of Tranaction Inter-Arrival Time C. Impact of Diconnection Probability Percentage of Succefully Executed Tranaction Average Server Energy Conumption Percentage Mobile Hot Diconnection Probability Mobile Hot Diconnection Probability Figure 8: Impact of Diconnection Probability In thi experiment, the impact of mobile hot diconnection i tudied by varying the mobile hot diconnection probability. When the diconnection probability i.5, the erver are kept out of each other tranmiion range for 5% of the entire experimental run. When the probability for diconnection increae, the probability for node to be in different network partition alo increae. Thu, ome erver might not be able to provide data ervice to client that are in a different partition. Hence, the number of uccefully executed tranaction decreae with the increae in the probability of mobile hot diconnection a een in Figure 8. A

10 expected, the power conumption of client i the maximum in a it uccefully execute the mot tranaction among all the three model. But yield the mot balance in energy conumption ditribution among erver. D. Impact of Number of Network Partition The impact of the number of network partition i hown in Figure 9. A the number of network partition increae, the number of uccefully executed tranaction decreae a erver in one network partition cannot provide data ervice to client/erver in other network partition. Server energy conumption ditribution become le balanced with the increae in the number of network partition a the iolated erver which hot hot data item conume higher power than the other iolated erver Percentage of Succefully Executed Tranaction Average Difference in Energy Conumption of two Server Number of Network Partition Number of Network Partition Figure 9: Impact of Number of Network Partition VII. CONCLUSIONS AND FUTURE WORK A data replication technique called for realtime mobile ad-hoc network databae ytem wa propoed in thi paper. By replicating hot data item at appropriate erver baed on the data model, real-time tranaction model, read/write tranaction model, current network topology, tability of wirele link, data acce frequencie, and erver remaining power, wa demontrated to perform the bet in term of percentage of ucceful tranaction, energy conumption and ditribution among node. A part of our future reearch, we plan to extend for group-baed MANET architecture. We will alo combine data caching and data replication for further improvement. REFERENCES [1] Cico, Nov. 24. [2] DALP, Nov 24 [3] Dell, Dell Uer Guide, 24. [4] IETF MANET Home Page - Dec 23. [5] T., Replica Allocation Method in Ad Hoc Network with Data Update, ACM-Kluwer Journal on Mobile Network and Application, Vol. 8, No. 4, Aug. 23, pp [6] T., Y.H.Loh, S.Nihio, Data Replication Method Baed on the Stability of Radio Link in Ad Hoc Network, Journal of the Information Proceing Society of Japan, Vol.44, No.9, Sept. 23, pp [7] M. Haupie, D. Simplot, J. Carle, Replication deciion algorithm baed on link evaluation ervice in MANET, Technical Report, LIFL Univ, May 22. [8] X. Hong, M.Gerla, G.Pei, and C.Chiang, A group mobility model for ad-hoc wirele network, ACM/IEEE MSWiM, Seattle,Wahington, 1999, pp [9] J. Gray, P. Helland, P. O Neil, and D. Shaha, The Danger of Replication and a Solution, ACM SIGMOD Int. Conference on Management of Data, June 1996, pp [] Hewlett-Packard Laboratorie, Energy Management on Handheld Device, Nov. 24. [11] G. Karumanchi, S. Muralidharan, R. Prakah, Information Diemination in Partitionable Mobile Ad Hoc Network, Sympoium on Reliable Ditributed Sytem, 1999, pp [12] C. N. Lau, Handling mobile hot diconnection, data caching, and data replication in managing real-time tranaction for mobile ad-hoc network databae, Mater Thei, Univerity of Oklahoma, Aug. 22. [13] Y.Li, Data Caching in Mobile Ad-Hoc Databae, Mater Thei, The Univerity of Oklahoma, May 24. [14]Lucent, lucent.com/pre/4/44.na.html, 4 [15] J.Luo, J.Pierre, H.P.Eugter, PAN:Providing reliable torage in ad-hoc network with probabilitic quorum ytem, ACM/SIGMOBILE Sympoium on Mobile Ad Hoc Networking & Computing, 23, pp [16] MySQL Open Source Databae Server, Nov. 24. [17] P. Padmanabhan, : Data Replication in Ad- Hoc Mobile Network Databae, Mater Thei, Univerity of Oklahoma, Dec. 24. [17b] P. Padmannabhan, L. Gruenwald, : A Data Replication for Real-Time Ad-Hoc Mobile Network Databae, IEEE Int. Conference on Data Engineering, April 26, pp [18] D. Ratner, P. Reiher, G.J. Popek, Roam: A Scalable Replication Sytem for Mobility, Mobile Network and Application, Vol. 9 No. 5, Oct. 24. [19] B.Xu, O.Wolfon, S.Chamberlain, Y.Yeha, Adaptive Lazy Replication in Unreliable Broadcat Network, Conference on Extending Databae Technology,2.