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An Adaptive and Multi-Service Routing Protocol for Wireless Sensor Networks

An Adaptive and Multi-Service Routing Protocol for Wireless Sensor Networks. Dr. Jaydip Sen Innovation Lab, Tata Consultancy Services, Kolkata, India Email: Jaydip.Sen@tcs.com. Purpose of the Work.

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An Adaptive and Multi-Service Routing Protocol for Wireless Sensor Networks

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  1. An Adaptive and Multi-Service Routing Protocol forWireless Sensor Networks Dr. Jaydip Sen Innovation Lab, Tata Consultancy Services, Kolkata, India Email: Jaydip.Sen@tcs.com

  2. Purpose of the Work To design and develop a query-based adaptive routing protocol that can satisfy multiple quality-of-service (QoS) requirements such as reliability and latency in Wireless Sensor Networks (WSNs). The algorithm does not involve any complex computations and hence it is highly energy-efficient. Key features: Scalability Robustness  based on multi-path communication and works even in presence of malicious nodes in the network Reliability Efficiency Low communication and computational overhead

  3. Outline of the Talk Wireless Sensor Networks (WSNs) Routing challenges in WSNs Proposed routing protocol Assumptions in the protocol design Algorithms for different application classes Applications with no reliability and latency requirements Applications with reliability requirement but no latency constraints Delay sensitive applications without any reliability requirements Delay-sensitive applications with reliability requirements Simulations and results Conclusion

  4. Wireless Sensor Networks (WSNs) WSNs are highly distributed networks consisting of a large number of tiny, low-cost, light-weight wireless nodes deployed to monitor an environment or a system. Each node consists of three subsystems: Sensor subsystem senses the environment Processing subsystem performs local computations on the sensed data Communication subsystem responsible for message exchange with neighboring sensor nodes While an individual sensor node has limited sensing region, processing power, and energy, networking of a large number of sensor nodes gives rise to a robust, reliable, and accurate sensor network covering a wide region.

  5. Routing Challenges in WSNs Due to large number of sensor nodes, a global addressing scheme cannot be applied and hence IP-based protocols are usually not applicable to these networks. In contrast to other wireless networks, applications in WSNs require flow of sensed data from multiple sensor nodes (sources) to a particular base station (BS). Sensor nodes are tightly constrained in terms of energy, processing, and storage capacities and a routing protocol should minimize the resource consumption in terms of CPU cycles and communication bandwidth. Data collected by many sensors in WSNs is typically based on common phenomena. Hence, there is a high probability that these data have some redundancy. Such redundancy needs too be exploited by the routing protocol so as to improve the energy-efficiency and bandwidth utilization.

  6. The Proposed Routing Protocol A large number of routing protocols for WSNs currently exists in the literature. These protocols can be classified into the following categories: Multipath protocols Query-based protocols QoS-based protocols This work presents a query-based adaptive routing protocol that can satisfy multiple QoS requirements such as reliability and latency. The algorithm does not involve any complex computations, and therefore, it is highly energy-efficient.

  7. The Proposed Protocol - Assumptions A node in the WSN, known as the sink node, floods the network with query messages periodically. In response to the query from the sink node, some nodes send back their responses. These nodes are called the source nodes. The wireless links connecting the sensor nodes are assumed to be symmetric. A query-based data gathering model is used. The source nodes send responses to the sink node only on receiving the query. No in-network processing is assumed. However, the proposed protocol will work even in situations where in-network processing and data aggregation is done at some intermediate sensor nodes. The sink has an external power source. The other sensor nodes are battery-driven. All nodes are static and each node has a unique identifier. Each sensor can transmit at one of the two pre-defined power levels – one for short-range and the other for long-range communications.

  8. The Proposed Protocol – Types of Applications The protocol distinguishes following four QoS classes of applications: Normal applications (Class I) do not require any guarantee (i.e. reliability) of packet delivery and do not have any latency constraints Reliable applications (Class II)  require guaranteed delivery of query messages from the sink to the sources and response messages from the sources to the sink, without any constraints on latency in packet delivery Delay-sensitive, real-time applications with no specific reliability requirements (Class III)  these applications are time-critical Delay-sensitive real-time applications with specific reliability requirements (Class IV)  packets from the sink to the sources and in the reverse path must traverse within a specific delay bounds and with a very high probability of successful delivery at the destination node

  9. The Proposed Protocol – Class I Applications When the sink requires information from the source nodes, it broadcasts a DATA_REQ message- essentially an IP packet. The type of service (ToS) bits in the DATA_REQ header is set to “00” so that all nodes receiving the packet understand that the packet is for a normal application. A typical DATA_REQ packet header contains the following additional information: (i) energy-level of the node, (ii) minimum hop-count of the node from the sink, (iii) node identifiers of three neighbors of the node that have least-hop counts from the sink. As the routing information is updated in all the nodes, each node creates and populates a table maintained locally. This table is called forwarding information table (FIT) A typical forwarding information table (FIT)

  10. The Proposed Protocol – Class I Applications Let the hop-count field in the DATA_REQ header from a neighbor node k to a node i be Lk, and the hop-count of node i from the sink be Hi. When a DATA_REQ packet traverses from say, node k to node i, FIT of node i is updated as follow: If ,the value of Hi is substituted by that of Lk + 1. If FIT of node i currently has no record for node k, a new entry for node k is created. The Hifield is updated based on the DATA_REQ packet, and the packet is broadcasted in the neighborhood of node i. If ,a new entry for node k is created in FIT of node i. The hop-count field is updated with the Hi value in DATA_REQ packet and the packet is broadcasted in the neighborhood of node i. If , the DATA_REQ packet is dropped at node i without any further broadcasting, because the distance of node k from which the DATA_REQ has arrived is further away from the sink than node i.

  11. The Proposed Protocol – Class I Applications When node i receives a DATA_REQ packet for which it is the intended source node, it send the response in the form of a DATA_REP packet. For routing the DATA_REP packet to the sink, node i uses the following algorithm. Routing algorithm 1 Let Nibe the set of neighbors of a node j where i {1, 2, 3 …., n}. Let Fjm be the set of forwarders for node j in the FIT where m {1, 2, 3}. Let Ej represents the energy level of node j. Step 1: Select Nx,Ny, Nz Ni from the FIT of node j such that their corresponding hop-counts Hx, Hy, and Hz are of the minimum value. Step2: Select Nk, where k  {x, y, z} and Ek is maximum. if Fkm ∩ Ni= = Φ, then forward the data packet to Nk. else Ni = Ni– Nk. Repeat Step 1.

  12. The Proposed Protocol – Class II Applications Reliability is the prime concern for these applications. Reliability is achieved by enhancing the (i) reliability of the routing paths, and (ii) reliability of packet delivery. The algorithm has three modules: Primary path selection Selection of alternate paths at the source node Selection of alternate paths at the intermediate nodes

  13. The Proposed Protocol – Class II Applications Primary path selection The source node i checks FIT to find its upstream neighbor with least hop-count from the sink, and forwards the packet to that neighbor if Ei≥ Ethreshold, where Eiis the energy of node i and Ethreshold is the minimum energy-level required for a node to receive and forward the data packet. In case of a node failure, the intermediate downstream node finds a new path to the sink by selecting the node with the least hop-count from the source after checking the entries in its FIT. Alternate path selection at the source The source node selects its upstream neighbors as follows: Select N1a , N2a (N – Np), where N is the set of all upstream neighbors of node i, Np is the upstream neighbors in the primary path and N1a and N2a are upstream neighbors for the source node in the first alternate path and second alternate path respectively. N1a and N2a are chosen on the basis of their least hop-count information maintained in the FIT of node i.

  14. The Proposed Protocol – Class II Applications Alternate path selection at intermediate nodes Due to the broadcast nature of wireless communications, the header information of a packet forwarded by a node is accessible to all nodes in its neighborhood. Looking at the header, it is possible for a node to know whether it lies on the path from a particular source to the sink. Based on the packet forwarding information collected over a period of time, the intermediate nodes construct path construction tables (PCTs) . These PCTs are used for identifying alternate paths to the sink at the intermediate nodes. When an intermediate node receives a packet, the node consults its FIT to select a node and checks with the PCT to ensure that the selected node is not in the path from that particular source node. A typical path construction table (PCT)

  15. The Proposed Protocol – Class II Applications Routing algorithm 2 Let Ni be the set of neighbors of a node j where i {1, 2, 3….n}. Let Cibe the list of records of nodes in the PCT which are in the path of a particular source-destination pair. Let Psa and Pda be the source and destination address in the DATA_REP packet from the source to the destination. Step 1: Select NxNi from the FIT such that its corresponding hop-count Hx is the minimum. Step 2: If (Ci∩ Nx = = Φ) choose Nx as the forwarding node; make the corresponding updates in the PCT; else if (Cisa == Psa && Cida == Pda) Ni = Ni– Nx ; repeat Step 1; else choose Nx as the next forwarding node; make the corresponding entry in the PCT;

  16. The Proposed Protocol – Class III Applications Routing algorithm 3: Let Nj be the set of neighbors of a node i where j {1, 2, 3, …n}. Let Ti represents the average waiting time for a packet in the queue for the node i. The information about the buffer occupancy (queue length) of each neighbor is broadcasted in node i’s neighborhood when FIT information is exchanged. Step I : Select Nx, Ny, Nz Ni from the FIT of the node i such that their corresponding hop-counts Hx, Hy, and Hz are minimum. Step II : Select Nk, k {x, y, z} such that Tk is the minimum. Since the largest component of the overall delay that a packet experiences is caused due to waiting in the buffers at the intermediate nodes, the delay is minimized by choosing those forwarder nodes that have least waiting time (i.e. smaller queues of packets in their buffers).

  17. The Proposed Protocol – Class IV Applications Primary path selection Let Nj be the set of neighbors of a node i where j  {1,2, 3,….n}. Let Ti represents the average waiting time for a packet in the queue for the node i. Select Nx, Ny, Nz Nj from the FIT of node i such that their corresponding hop-counts Hx, Hy, and Hz are minimum. Selection of alternate path at the source node The source selects the upstream neighbors from its FIT as follows : Select Na (N – Np) where Np is the upstream neighbor of the source node in the primary path and Na is the upstream neighbor for the source in the alternate path having the next least average waiting time. Alternate path selection at the intermediate nodes the approach is same as for applications belonging to Class II. However, in this case, the node selection is based on the average waiting time of the packets in the buffers of the intermediate nodes and not on the hop-counts.

  18. Simulation and Results The protocol is simulated using network simulator ns2 (version 2.3.2) Two metrics are chosen for performance analysis Average dissipated energy in sensor nodes ratio of the total energy dissipated in the network to the number of packets received by the sink over a given period of time. Average latency in message communication average end-to-end delay a packet experiences while traversing from source to the sink. Initially, 50 sensor nodes are randomly distributed on a 70m * 70m area. The area of deployment is increased as more nodes are added to maintain constant node density. The number of nodes in the network is increased from 50 to 150 with 25 nodes being added in every step of increment. For each configuration, 10 simulation runs were executed and the computed average value is taken as the final observation. The radio-range for each sensor  15m for Class I and II; 30m for Class III and IV. In each simulation run, one node is chosen as the sink and three nodes are randomly chosen as the sources. Each source sends three reply packets for every query it receives to ensure high probability of receiving at the sink.

  19. Simulation and Results (contd.) Average dissipated energy in a node with varying network sizes

  20. Simulation and Results (contd.) Average delay experienced by a message in different network sizes

  21. Simulation and Results (contd.) Probability of successful packet delivery with 10% nodes failed

  22. Simulation and Results (contd.) Probability of successful packet delivery with 20% nodes failed

  23. Observations Case III results in the minimum latency since it does not guarantee any reliability but uses higher transmit energy to reduce number of hops. Case II has the highest latency since it identifies multiple paths for reliability. Case IV has higher latency than Case III since it also uses multipath. Case I causes more delay than Case IV since it uses less transmit power. However, it has less latency than Case II since it does not use multipath. Case I is the most energy-efficient. Case II consumes more power than Case I since it uses multipath. Case III requires higher transmit power to reduce delay and hence consumes more power than Case II. Case IV leads to maximum dissipation of power as it ensures both high reliability and less latency. Case II always guarantees 100% delivery of the DATA_REP packets to the sink since any failed node is detected beforehand and packets are routed in alternate paths. Case II is thus taken as the base for comparing the other three cases. Case IV uses multiple paths but some packets are lost due to delay constraints. Case III provides more reliability in terms of packet delivery to the sink than Case I. Case III involves less number of nodes for forwarding a packet from a source to the sink. Thus, with the same percentage of failed nodes, the probability of Case I will encounter a failed node will be higher.

  24. Simulation and Results (contd.) Comparison of the proposed protocol with PEGASIS

  25. Observations For comparison with PEGASIS, all the sensor nodes are deployed in such a way that they can directly access the BS (sink). Random graphs are generated with 100 nodes distributed over a 50m * 50m region. With varying percentages of failed nodes, it is clear that the proposed algorithm provides longer network life-time.

  26. Conclusion and Future Work A query-based, adaptive routing protocol is presented that satisfies QoS requirements such as reliability and latency. For ensuring path reliability, the protocol uses multiple paths from source nodes to the sink nodes and for guaranteeing data reliability, it sends multiple copies of the same message. The latency is minimized by enabling sensor nodes to transmit with higher power levels. The protocol is simulated on network simulator ns2 and its performance is compared with an existing protocol – PEGASIS. The performance of the protocol is found to be better. As a future scope of work, the query-driven protocol may be made event-driven so as to make it proactive.

  27. Thank You

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