Manet: Routing and Quality of Service Metrics

Transcription

1 Manet: Routing and Quality of Service Metrics Manet: Routing and Quality of Service Metrics Juhi Singla B.M.College of Engg. & Tech. (Sonepat) R.K. Gupta, Ritu Goyal, and Anuj Jain T.C.M. College of Engineering (Sonepat) ABSTRACT: A Mobile Ad hoc Network (MANET) is a collection of wireless mobile nodes forming a self-configuring network without using any existing infrastructure. The rapidly changing and unpredictable nature of Mobile Ad-hoc Networks (MANET) pose a wide range of challenges like efficient routing, load distribution, congestion avoidance, energy consumption, etc. This paper deals with the optimization of multi hop routing using metaheuristic algorithm of shortest path using ACO and also the QoS of MANET has been discussed. Keywords: MANET, ACO, QoS 1. INTRODUCTION Ad Hoc means improvised or not organized which often has a negative meaning but the sense in this context is not negative but only describing the dynamic network situation. Ad hoc networks is the construction of temporary networks with no wires, no communication infrastructure and no administrative intervention required [4]. A MANET is an autonomous system of mobile nodes connected by wireless links. The ad-hoc networks are classified into two groups: single hop and multi hop networks. In single hop networks the nodes are within their R range and hence communicate with each other directly while in multi hop ad-hoc network nodes are willing to act as a routers and route or forward the traffic of other nodes. Developing support for routing is one of International Journal of Logic Based Intelligent Systems, Vol. 1, No. 1, Jan-June

2 Juhi Singla, R.K. Gupta, Ritu Goyal, and Anuj Jain the most significant challenges in ad hoc networks and is critical for the basic network operations. Certain unique combinations of characteristics make routing in ad hoc networks interesting. irst, nodes in an ad hoc network are allowed to move in an uncontrolled manner. Such node mobility results in a highly dynamic network with rapid topological changes causing frequent route failures. A good routing protocol for this network environment has to dynamically adapt to the changing network topology. Second, the wireless channel provides much lower and more variable bandwidth than wired networks. The wireless channel working as a shared medium makes available bandwidth per node even lower. Third, nodes run on batteries which have limited energy supply. In order for nodes to stay and communicate for longer periods, it is desirable that a routing protocol be energy-efficient as well [7]. This also provides another reason why overheads must be kept low. Thus, routing protocols must meet the conflicting goals of dynamic adaptation and low overhead to deliver good overall performance. Optimization of routing is emerging challenge, a metaheuristic is an iterative master process or a set of algorithmic concepts that guides and modifies the operation of subordinate heuristics to efficiently produce high quality solutions. The main representatives of this computational paradigm are Genetic Algorithms (GAs), Evolution Strategies (ESs) and Evolutionary Programming (EP), which was developed independently of each other. The concept of Ant Algorithms was first introduced in [6] and since that time, it has been applied to both theoretical and practical optimization problems with great success. Ant algorithms are an iterative, probabilistic meta-heuristic for finding solutions to combinatorial optimization problems. (A) Mobile Ad hoc Network Ad hoc networks are classified according to their coverage area BAN (Body area Network) is strongly correlated with wearable computers and provides connectivity among the devices like earphones, microphones etc. Communication range is 1-2 m. PAN (Personal 34 International Journal of Logic Based Intelligent Systems, Vol. 1, No. 1, Jan-June 2011

3 Manet: Routing and Quality of Service Metrics Area Network) connect mobile devices carried by users to other mobile and stationary devices. LANs (WLAN) hane a communication range typical of a single building or a cluster of buildings that is m. Number of active nodes is the other metric used to classify MANETs that is Ad hoc network as a Small Scale (that is 2-20 nodes), Moderate Scale ( nodes), Large Scale (100+ nodes) and a Very Large Scale (1000+ nodes). (B) Properties of MANETs Dynamic Topology: The link connectivity among the terminals of the network varies dynamically and unpredictably. There could be frequent disconnections among the nodes,this means that the topology is dynamic and routes that existed may not exist some time later due to the movement of the intermediate nodes. To alleviate this problem, the protocol should be resilient to topology changes. Bandwidth: MANETs have significantly lower bandwidth capacity in comparison with fixed networks. Current technologies suitable for the realization of MANETs are IEEE (b,a) with bandwidth upto 54 Mbps and Bluetooth (1 Mbps) the channel over which the terminals communicate is subjected to noise, fading and interference, and has less bandwidth than a wired network. Energy: MANETs have problem of energy conservation as all mobile nodes get their energy from batteries, which is a scarce resource. Security: The nodes and the information in MANETs are exposed to certain threats like denial of service attacks, eavesdropping, spoofing and denial of service attacks etc. Also mobility implies higher security risks than static operation because portable devices may be stolen or their traffic may insecurely cross wireless link Autonomous: No Centralized infrastructure is available. Each mobile node is a n autonomous node which may function both as a host as well as a router. International Journal of Logic Based Intelligent Systems, Vol. 1, No. 1, Jan-June

4 Juhi Singla, R.K. Gupta, Ritu Goyal, and Anuj Jain Distributed Operation: No centralized control is provided for the management of the network. All control is self configured among the nodes where each node acts as a relay. Multi hop Routing: or delivering the data packets from a source to its destination (not in the R range), the packets should be forwarded via one or more intermediate nodes where each node acts as a router. Light Weight Terminal: Mobile devices in MANET have a less CPU processing, low power storage and small memory size and hence they are light in weight. Routing: Routing is the task of directing data flow from source to destination and hence maximizing the network performance. Proactive routing uses periodic messages to distribute information about the current network topology. The aim is to have a valid route to each destination. Therefore the nodes remain always updated about the change in the topology [2]. Reactive routing work by computing the route only when it is needed. So, when a node has a packet to transmit, It first discovers the route to the destination and then sends out the message. Hybrid Routing combines the advantages of both proactive and reactive protocols example. Zone Routing Protocol (ZRP). In this, a network is divided into Zones. Within the Zone, Reactive routing protocols are used and the Inter-Zone messages must be routed via the Zone gateway. The key parameters that should be kept in mind while designing a routing protocol are as Effective routing: or successful discovery and delivery of the packet from source to destination some measures are taken into account. These are packets delivery ratio, percentage of optimal routes taken and average end to end delay. Congestion avoidance: The routing protocol should not congest a particular route /node thereby leading to packet drop or failure of node. 36 International Journal of Logic Based Intelligent Systems, Vol. 1, No. 1, Jan-June 2011

5 Manet: Routing and Quality of Service Metrics Energy consumption: It must minimize the energy consumption of the individual nodes as in the case of laptops, PDA etc. Load balancing: Distributing the load to all possible nodes without overloading some specific nodes present in the optimal routes of communication. Mobility: It is the movement of a node out of or into the communication range of other nodes changes not only it's neighbor relationships with other nodes, but also all routes based on the relationships forperformance evaluation we use various mobility model. 2. META HEURISTIC A metaheuristic is an iterative master process or a set of algorithmic concepts that guides and modifies the operation of subordinate heuristics to efficiently produce high quality solutions. It may manipulate a complete (or incomplete) single solution or a collective solution at each iteration. The subordinate heuristic may be high or level procedures, or a simple local search, or just a construction method. (A) Stigmergic Learning and ACO Routing Stigmergy is a form of a distributed control based on indirect communication among agents which locally modify the environment and react to these modifications leading to a phase of global co-ordination of the agents actions. An example of stigmergic process is to find out the shortest path between their nests and food source by the ants. A volatile scent like chemical substance called pheromone is the stigmergic variable. The individual messages are passed between ants leading to a co-ordinated work control of ants without the presence of a centralized control system. Initially the ants spread out in all the directions in search of food. On returning back after finding the food ants mark the trail with the pheromones. These pheromones are dropped at regular interval to act as a trail[1]. Ants moving back and forth preferentially move towards areas of higher pheromone intensity. Shorter paths are covered quickly and hence have higher pheromone concentration as shown in ig 1. These shorter paths attract more and more ants. International Journal of Logic Based Intelligent Systems, Vol. 1, No. 1, Jan-June

6 Juhi Singla, R.K. Gupta, Ritu Goyal, and Anuj Jain igure 1: Routing by Ants (B) Routing Algorithms The challenges in MANETs are providing active network management and simply routing. The steps included in the algorithm are: (a) Node level Congestion Measurement : Every node calculates a Node Congestion Metric which gives an indication on the amount of congestion at the node. This metric varies between 0(Very high congestion) to 1(Least congestion). It is based on the buffer occupancy, channel load measurement and packet drop rate. (b) Route Discovery: irst the source checks for the existing routes. When no routes are known, It broadcasts the orward Request Ants which are propagated through the network till it reaches the destination. Then, the destination node sends the Backward Ants for every orward Request Ants that it receives. The source chooses the shorter path to the destination with the assumption that the same helps in reducing energy and time. 38 International Journal of Logic Based Intelligent Systems, Vol. 1, No. 1, Jan-June 2011

7 Manet: Routing and Quality of Service Metrics (c) Calculation of Route Efficiency Metric: Whenever a node sends a packet, the packet has a metric value called the Route Efficiency Metric (REM). The source who originates the packet initially has its value 1 although it may be less than 1. When the packet is being forwarded/broadcasted, all the intermediate nodes multiply the REM with the individual Node Congestion Metrics. Then the REM can be defined as Route Efficiency Metric = (Node Congestion values of intermediate nodes from source to destination) The individual node congestion metric is simply the probability that a node can forward a packet successfully to the next hop. Node Congestion Metric is considered to be linear but it produces incorrect results, as high values of node congestion have the same impact on the overall congestion (like 0.1 or 0.005). Hence, the algorithm converts the linear weights of Node Congestion Metric to a non-linear weight using the equation New Node Congestion = (1 (1 Node Congestion)3) Due to non-linear scale, higher values of Node Congestion have a lesser impact. (d) Probabilistic Route Choosing Algorithm: In this initially the pheromone scents are calculated for every route to a particular destination and then probabilistically a route is chosen based on the Pheromone values. (e) Pheromone Count of Route = (REM)*L Where REM = Route Efficiency Metric L = Length of the Route Probability of Route= Pheromone Count of Route/ (Pheromone count of all routes to destination) Route Maintenance: In MANETs network topology changes frequently due to high and random mobility of nodes. To International Journal of Logic Based Intelligent Systems, Vol. 1, No. 1, Jan-June

8 Juhi Singla, R.K. Gupta, Ritu Goyal, and Anuj Jain 3. QOS find the goodness of the route, it is needed to update the pheromone level for the different routes. To accomplish this, when a destination node receives a packet, it probabilistically send a congestion update message, the REM value is updated and given by New REM value = α * (Old REM Value) + (1 α) *REM When located at a node i an ant k uses the p k ij = τ α ij k l N i 0 40 International Journal of Logic Based Intelligent Systems, Vol. 1, No. 1, Jan-June 2011 τ α il if j N if j N pheromone trails to compute the probability of choosing j as the next node where N is the neighborhood of ant k when in node i. When the arc (i, j) is traversed, the pheromone value changes as follows: The United Nations Consultative Committee for τ ij τ ij + τ k International Telephony and Telegraphy (CCITT) Recommendation E.800 has defined QoS as: The collective effect of service performance which determines the degree of satisfaction of a user of the service. This is a widely accepted definition since it doesn't makes any reference to any minimum characteristics, such as Bandwidth or Delay, or mechanisms, such as Admission Control, SLA, Signaling Protocol. (A) IP QoS Network traffic Engineering has two approaches for achieving QoS which are complementary, designed for use in combination for different network contexts. These are ( a) Reservation-based Engineering and (b) Reservation-less Engineering. k i k i

9 Manet: Routing and Quality of Service Metrics In Reservation-based Engineering, network resources are apportioned according to an application s QoS request and subject to bandwidth management policy. This approach was used in ATM (Asynchronous Transfer Mode) and is today the method of achieving QoS in RSVP-IntServ. In Reservation-less Engineering on the other hand no reservation is done within the network. QoS is achieved by the addition of smart mechanism into the network such as Connection Admission Control (CAC), Policy Managers, Traffic Classes, Queuing Mechanisms. CAC controls which nodes can access the network and it will assure to a node that once it is granted access to the network, it will be served with the QoS parameters it is requesting. Policy Managers ensure that no node will violate the type of service it is pre-assigned. Traffic Classes, such as assured, controlled-load or best-effort services, differentiate the processing priority of data packets. Queuing mechanisms are responsible for dropping the packets with the lowest priority in the case of congestion or to provide explicit feedback to nodes in order to avoid congestion. (B) QoS Models for MANets igure 2: IPv4 Packet The QoS Model specifies the architecture which will enable us to offer services that operate better than the current "best effort" model that exists in MANets. This architecture should take into consideration the challenges of Mobile Ad Hoc Networks e.g. dynamic topology and time-varying link capacity. IntServ/RSVP model is not suitable for MANets due to the resource limitations in MANets. There are several factors which prohibit the use of that model over a MANet. 1) Huge storage and processing overhead for each mobile host, since they have to build and maintain such International Journal of Logic Based Intelligent Systems, Vol. 1, No. 1, Jan-June

10 Juhi Singla, R.K. Gupta, Ritu Goyal, and Anuj Jain information. Moreover the amount of state information increases proportionally with the number of flows, which is also a problem with the current QoS Internet, but which will be fortunately solved with the aggregation of state information on the core routers (DiffServ). 2) The RSVP reservation and maintenance process is a network consuming procedure. Thus RSVP signaling packets will grapple with the data packets for resources and more specifically for bandwidth. This happens because RSVP is an out-of-band signaling protocol. 3) In order to have a complete QoS Model mechanism such as Connection Admission Control (CAC), classification and scheduling must be provided. These mechanisms though require again a respectable amount of network resources which are usually not available in MANets. DiffServ on the other hand is a lightweight model for the interior routers since individual state flows are aggregated into set of flow as shown in ig. 3. This igure 3: In DiffServ Interior lows are Aggregated makes routing a lot more easily in the core of the network. Thus this model could be a potential model for MANets. In MANets though there is no clear definition of what is a core, ingress or egress router because of the dynamic topology of the network. This drawback would again take us back to the IntServ model where several separate flow states are maintained, causing a heavy storage cost in every node. Moreover the concept of the Service Level Agreement 42 International Journal of Logic Based Intelligent Systems, Vol. 1, No. 1, Jan-June 2011

11 Manet: Routing and Quality of Service Metrics (SLA), defined in Wire-based QoS models is not more applicable. SLA basically defines the contract between the customer (e.g. ISPs) and the clients. The charging model in MANets has still a long way to go and could be characterized as a gray area. In a completely ad-hoc topology where there is no concept of service provider and client and where there are only clients it would be quite difficult to innovate QoS, since there is no obligation from somebody to somebody else making QoS almost infeasible. lexible QoS Model for MANets (QMM), is the first QoS Model proposed for MANets in The idea of the paper is to combine knowledge from the solutions offered in the wire-based networks and apply them to a new QoS Model which will take into consideration the characteristics of MANets. The basic idea of that model is that it uses both the per-flow state property of IntServ and the service differentiation of DiffServ. In other words, this model proposes that highest priority is assigned per-flow provisioning and other priority classes are given per-class provisioning. This model is based on the assumption that not all packets in our network are actually seeking for highest priority because then this model would result in a similar model with IntServ where we have per-flow provisioning for all packets. The QMM hybrid model defines three types of nodes, exactly as in DiffServ ( a) ingress, (b) core and (c) egress as shown in ig. 4. The difference though is that in QMM the type of a node has nothing to do with its physical location in the network, since this wouldn't make any sense in a dynamic network topology. A node is characterized as ingress if it is transmitting data, core if it is forwarding data and egress if it is receiving data. igure 4: In the irst Scenario Nodes 2,3,6 Act as Interior (Core) Nodes and in the Second Scenario 2 Only Node 3 Act as a Core Node International Journal of Logic Based Intelligent Systems, Vol. 1, No. 1, Jan-June

12 Juhi Singla, R.K. Gupta, Ritu Goyal, and Anuj Jain 4. CONCLUSION In this paper a routing algorithm for MANETs which was inspired by ideas from Swarm Intelligence, and more specifically by the framework of ACO. This proposed algorithm determines the shortest path from source to destination in an efficient way so as to reduce the end to end delay. The QoS models for Manet have also been discussed. In the future the simulations would be performed on the NS2 Simulator and the results would be compared with the AODV, DSR and other protocols. REERENCE [1] A C Jawahar, Ant Colony Optimization for Mobile Adhoc Networks pp-1 to 6, Department of Electrical Engineering, Rutgers. [2] Di Caro Gianni, Ducatdle rederick and Gambardella Luca Maria, Swarm Intelligence for Routing in Mobile Ad hoc Networks, 2005 IEEE. [3] Kwak Byung-Jae, Regular Member, Nah-Oak SONG, and Leonard E. Miller, Non Members, A StandardMeasure of Mobility for Evaluating Mobile Ad-hoc Network Performance, IEICE Trans.Commun., VOL. E86-B, No.11 November [4] Tarek Helmi ABD El-Nabi Ali Ahmed, A Dissertation on Modeling and Simulation of a Routing Protocol for Ad-hoc Networks Combining Queuing Network Analysis and Ant Colony Algorithms April [5] S. Radha and N. Ravindram, A New Solution to Improve the Link ailure Tolerance in Mobile Ad-hoc Networks Paper No. 165-B, IETE Journal of Research, 53, No. 4, July-August 2007, pp [6] M. Dorigo "Ant Colony Optimization" PHI Publications. [7] P. Mohapatra and S. Krishnamurthy, AD HOC NETWORKS Technologies and Protocols 2005 Springer Science + Business Media, Inc. [8] Demetrios Zeinalipour-Yazti, A Glance at Quality of Services in Mobile Ad-Hoc Networks, inal Research Report for CS260- Seminar in Mobile Ad Hoc Networks, all 2001, November 19, International Journal of Logic Based Intelligent Systems, Vol. 1, No. 1, Jan-June 2011