UNIT V ROUTING PROTOCOLS FOR WSN

Transcription

1 UNIT V ROUTING PROTOCOLS FOR WSN Created by : Neha Birla 1

2 Data Dissemination and Gathering Dissemination = The act of spreading something, spreading, distribution. Gathering = Assemble or collect 2

3 1. Data Dissemination Process of Distribution of data. Information flow from one sensor node to another. The originator of data is known as Source Node and Receiver of the data is called Sink node or Gateway. The Sink registers its interest to receive the data from source. The Source reports the data information to the Sink. The information thus reported is called event. 3

4 Process of Data Dissemination The node that is interested in some events, like temperature or air humidity, broadcasts its interests to its neighbors periodically. Interests are then propagated through the whole sensor network. Nodes that have requested data, send back data after receiving the request. Intermediate nodes in the sensor network also keep a cache of received interests and data. 4

5 Data Dissemination Methods Flooding Gossiping SPIN 5

6 1.1 Flooding Each node which receives a packet (queries/data) broadcasts it if the maximum hop-count of the packet is not reached and the node itself is not the destination of the packet. Advantage No costly topology maintenance or route discovery Disadvantages Implosion Overlapping Resource Blindness 6

7 Implosion : This is the situation When duplicate messages are send to the same node. This occurs 7 when a node receives copies of the same messages from many of its neighbors

8 Overlap : Overlap is another problem which occurs when using flooding. If two nodes share the same observation region both nodes will witness an event at the same time and transmit details of this event. Resource blindness : the flooding protocol does not consider the available energy at the nodes and results in many redundant transmissions. Hence, it reduces the network lifetime. 8

9 1.2 Gossiping Modified version of flooding The nodes do not broadcast a packet, but send it to a randomly selected neighbor. Avoid the problem of implosion by making one copy of each message at any node It takes a long time for message to propagate throughout the network. The hop count can become quite large due to the protocols random nature 9

10 1.3 Sensor Protocols for Information via Negotiation SPIN use negotiation and resource adaptation to address the disadvantage of flooding and Use meta-data instead of raw data. Reduce overlap and implosion, and prolong network lifetime. SPIN-1 has three types of messages: ADV, REQ, and DATA. SPIN-2 using an energy threshold to reduce participation. A node may join in the ADV-REQ-DATA handshake only if it has sufficient resource above a threshold. 10

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12 2. Data Gathering The objective of the data gathering problem is to transmit the sensed data from each sensor node to a BS. The goal of algorithm which implement data gathering is maximize the lifetime of network Minimum energy should be consumed The transmission occur with minimum delay 12

13 Difference between Data Dissemination and Gathering Data Dissemination 1 Any node can request the data along with base station. Data Gathering All data is transmitted to the base station 2 Data is always transmitted on demand Data can be transmitted periodically 13

14 Data Gathering Approaches Direct Transmission Power-Efficient Gathering for Sensor Information Systems Binary Scheme 14

15 2.1 Direct Transmission All sensor nodes transmit their data directly to the BS. It cost expensive when the sensor nodes are very far from the BS. Nodes must take turns while transmitting to the BS to avoid collision, so the media access delay is also large. Hence, this scheme performs poorly with respect to the energy x delay metric. 15

16 2.2 Power-Efficient Gathering for Sensor Information Systems PEGASIS based on the assumption that all sensor nodes know the location of every other node. Any node has the required transmission range to reach the BS in one hop, when it is selected as a leader. The goal of PEGASIS are as following Minimize the distance over which each node transmit Minimize the broadcasting overhead Minimize the number of messages that need to besent to the BS Distribute the energy consumption equally across all nodes 16

17 To construct a chain of sensor nodes, starting from the node farthest from the BS. At each step, the nearest neighbor which has not been visited is added to the chain. This algorithm uses greedy algorithm for chain construction. Before first round of communication chain formation is done During formation of chain care must be taken so that nodes already in chain should not revisited It is reconstructed when nodes die out. At every node, data fusion or aggregation is carried out. 17

18 A node which is designated as the leader finally transmits one message to the BS. 18 Leadership is transferred in sequential order. The delay involved in messages reaching the BS is O(N)

19 Figure 5 : Data gathering with PEGASIS 19

20 2.3 Binary Scheme This is a chain-based scheme like PEGASIS, which classifies nodes into different levels. This scheme is possible when nodes communicate using CDMA, so that transmissions of each level can take place simultaneously. The delay is O(log 2 N) 20

21 Advantages Low delay of only O(log2N), where the N is the amount of nodes. Disadvantages Non equal distribution of energy consumption, nodes that are active on several levels consume more energy than nodes that are only active at the first level. This might lead to the situation where some of sensor nodes die earlier than others. Transmission distances may become long in high levels, which leads to a high power consumption 21

22 Routing Challenges and Design Issues in WSN The design of routing protocols in WSNs is influenced by many challenging factors. These factors must be overcome before efficient communication can be achieved in WSNs. Node deployment Energy considerations Data delivery model 22

23 Node/link heterogeneity Fault tolerance Scalability Network dynamics Transmission media Connectivity Coverage Data aggregation/converge cast Quality of service 23

24 Node Deployment Node deployment in WSNs is application dependent and affects the performance of the routing protocol. The deployment can be either deterministic or randomized. In deterministic deployment, the sensors are manually placed and data is routed through pre-determined paths. In random node deployment, the sensor nodes are scattered randomly creating an infrastructure in an ad hoc manner. 24

25 Energy Considerations Sensor nodes can use up their limited supply of energy performing computations and transmitting information in a wireless environment. Energy conserving forms of communication and computation are essential. In a multi-hop WSN, each node plays a dual role as data sender and data router. The malfunctioning of some sensor nodes due to power failure can cause significant topological changes and might require rerouting of packets and reorganization of the network. 25

26 Data Delivery Model Time-driven (continuous) Suitable for applications that require periodic data monitoring Event-driven React immediately to sudden and drastic changes Query-driven Respond to a query generated by the BS or another node in the network Hybrid The routing protocol is highly influenced by the data reporting method 26

27 Node/Link Heterogeneity Depending on the application, a sensor node can have a different role or capability. The existence of a heterogeneous set of sensors raises many technical issues related to data routing. Even data reading and reporting can be generated from these sensors at different rates, subject to diverse QoS constraints, and can follow multiple data reporting models. 27

28 Fault Tolerance Some sensor nodes may fail or be blocked due to lack of power, physical damage, or environmental interferences It may require actively adjusting transmission powers and signaling rates on the existing links to reduce energy consumption, or rerouting packets through regions of the network where more energy is available 28

29 Scalability The number of sensor nodes deployed in the sensing area may be on the order of hundreds or thousands, or more. Any routing scheme must be able to work with this huge number of sensor nodes. In addition, sensor network routing protocols should be scalable enough to respond to events in the environment. 29

30 Network Dynamics Routing messages from or to moving nodes is more challenging since route and topology stability become important issues Moreover, the phenomenon can be mobile (e.g., a target detection/ tracking application). 30

31 Transmission Media In general, the required bandwidth of sensor data will be low, on the order of kb/s. Related to the transmission media is the design of MAC. TDMA (time-division multiple access) CSMA (carrier sense multiple access) 31

32 Connectivity High node density in sensor networks precludes them from being completely isolated from each other. However, may not prevent the network topology from being variable and the network size from shrinking due to sensor node failures. In addition, connectivity depends on the possibly random distribution of nodes. 32

33 Coverage In WSNs, each sensor node obtains a certain view of the environment. A given sensor s view of the environment is limited in both range and accuracy. It can only cover a limited physical area of the environment. 33

34 Data Aggregation/Convergecast Since sensor nodes may generate significant redundant data, similar packets from multiple nodes can be aggregated to reduce the number of transmissions. Data aggregation is the combination of data from different sources according to a certain aggregation function. Converge casting is collecting information upwards from the spanning tree after a broadcast. 34

35 Quality of Service In many applications, conservation of energy, which is directly related to network lifetime. As energy is depleted, the network may be required to reduce the quality of results in order to reduce energy dissipation in the nodes and hence lengthen the total network lifetime. 35

36 Routing Protocols in WSNs: A taxonomy Routing protocols in WSNs Network Structure Flat routing SPIN Directed Diffusion (DD) Hierarchical routing LEACH PEGASIS TTDD Location based routing GEAR GPSR Protocol Operation Negotiation based routing SPIN Multi-path network routing DD Query based routing DD, Data centric routing QoS based routing TBP, SPEED Coherent based routing DD Aggregation Data Mules, CTCCAP 36

37 Routing Strategies in WSN 37

38 Routing Strategies Aim to make communication more efficient Trade-off between routing overhead and data transmission cost Strategies incur differing levels of communication and storage overhead Hybrid approaches are possible 38

39 Proactive and Reactive Routing Proactive routing Routes created and maintained in advance E.g : LEACH protocol Does not scale to large networks Reactive routing Routes created and cached as required E.g : TEEN protocol Dynamic delays 39

40 Geographic and Energy Aware Routing Motivation: Reduce overhead of interest and low rate data flooding in directed diffusion Basic ideas: Leverage geographical information to restrict flooding, and recursively disseminate data inside the target region. Extend overall network lifetime using local techniques to balance energy usage Reuse routing information across multiple user queries. 40

41 Geographic and Energy Aware Routing Forward the packets towards the target region: Greedy mode: minimizing cost function (f=mix function of distance and energy) Route around communication holes with energy aware neighbor estimation Disseminate the packet within the target region: Geographic Recursive Forwarding recursively re-send packets to subregions of the original geographic region 41

42 Geographic and Energy Aware Routing Each node has a learned cost (historical cost) and an estimated cost (present state cost) to decide the next forwarding node Learned cost h( N, R) h( N, R) C( N, N ) min min Estimated cost c( N, R) d( N, R) (1 ) e( N ) i i i 42

43 Geographic Routing G P S R : G R E E D Y P E R I M E T E R S T A T E L E S S R O U T I N G F O R W I R E L E S S N E T W O R K S 43

44 Motivation A sensor net consists of hundreds or thousands of nodes Scalability is the issue Existing ad hoc net protocols, e.g., DSR, AODV, ZRP, require nodes to cache e2e route information Dynamic topology changes Mobility Reduce caching overhead Hierarchical routing is usually based on well defined, rarely changing administrative boundaries Geographic routing Use location for routing 44

45 Scalability metrics Routing protocol msg cost How many control packets sent? Per node state How much storage per node is required? E2E packet delivery success rate 45

46 Assumptions Every node knows its location Positioning devices like GPS Localization A source can get the location of the destination MAC Link bidirectionality 46

47 Geographic Routing: Greedy Routing Closest to D S A D - Find neighbors who are the closer to the destination - Forward the packet to the neighbor closest to the destination 47

48 Benefits of GF A node only needs to remember the location info of one-hop neighbors Routing decisions can be dynamically made 48

49 Greedy Forwarding does NOT always work GF fails If the network is dense enough that each interior node has a neighbor in every 2 /3 angular sector, GF will always succeed 49

50 Energy-Aware Routing Maximise network lifetime (no accepted definition) Communication is the most expensive activity Possible goals include: Shortest-hop (fewest nodes involved) Lowest energy route Route via highest available energy Distribute energy burden evenly Lowest routing overhead Distributed algorithms cost energy Changing component state costs energy NOTE: Read Routing Strategies PPT s after this 50

51 Energy-Aware Routing A destination-initiated reactive protocol It maintains a set of paths Choosing paths by means of certain probability depending on how low the energy consumption is 51

52 Energy-Aware Routing Setup Phase Directional flooding Local Rule Sensor p 1 = nj Controller p 2 = nj 52

53 Energy-Aware Routing Data Communication Phase Each node makes a local decision 0.3 Sensor Controller

54 Attribute-based routing Data-centric approach: Not interested in routing to a particular node or a particular location Nodes desiring some information need to find nodes that have that information Attribute-value event record, and associated query type animal instance horse location 35,57 time 1:07:13 type animal instance horse location 0,100,100,200 54

55 Directed diffusion Sinks: nodes requesting information Sources: nodes generating information Interests: records indicating A desire for certain types of information Frequency with which information desired Key assumption: Persistence of interests Approach: Learn good paths between sources and sinks Amortize the cost of finding the paths over period of use [IGE00] 55

56 Diffusion of interests and gradients Interests diffuse from the sinks through the sensor network Nodes track unexpired interests Each node maintains an interest cache Each cache entry has a gradient Derived from the frequency with which a sink requests repeated data about an interest Sink can modify gradients (increase or decrease) depending on response from neighbors 56

57 Directed Diffusion Rumor Routing Geographic hash table Attribute based Routing 57