Chapter 6 Route Alteration Based Congestion Avoidance Methodologies For Wireless Sensor Networks

Transcription

1 Chapter 6 Route Alteration Based Congestion Avoidance Methodologies For Wireless Sensor Networks Early studies shows that congestion avoid in wireless sensor networks (WSNs) is a critical issue, it will not only affect transmission reliability, and will waste valuable energy resources. In order to reduce the wireless sensor network routing instability, In this a changing routing congestion control protocol (CRCP) for WSNs is presented. In this protocol, a timely potential congestion detection technique based on cognition detection technology is developed. When the congestion happens unavoidably, CRCP is presented to reallocate traffic with changing route protocol to mitigate congestion and avoid conflict which will enhances data transmission reliability of Cluster head. Congestion data local preservation strategies, it effectively avoids data lost during the congestion period and guarantees the reliability of data transmission. The changing routing protocol also provides a network load balancing, effective prolongs the life cycle of the clusters, postpones network system lifetime. Rest of the chapter is organized as follows. Section 6.1 presents introduction. The network model for the developed protocol is given in Section 6.2. Section 6.3 deals with CRCP. Simulation results and discussion of CRCP is explored in section 6.4. Finally work of this chapter is summarized in Section Introduction Our aim is to find an optimal path to the gateway in terms of energy consumption while meeting the end-to-end delay requirements. End-to-end delay requirements are associated only with the real-time data. This protocol is a group of four algorithms flooding, Congestion detection, Changing route for congestion avoidance and Local data storage at sensor node. By applying these a good quality channel is made up of, which is giving minimum packet loss in minimum energy consumption Network Model We assume that sensor nodes are densely deployed in a highly dense field. Sensor nodes

2 will sense the environment and report to a sink in constant time intervals t. They are grouped into small clusters and each cluster has a cluster head (CH), which is responsible for data gathering from the cluster members and perform the duty of a routing node by forwarding collected data towards the sink. The lifetime of sensor node is depends on the battery life. Figure 6.1. Optional Path Tree At each round the network establishes a new routing topology by setting up new cluster head optional routing paths. To set up such routing paths, the base station initiates a route setup phase by advertising a route update (with its hop count = 0) to be flooded through the network. Then, each receiving CH records the CH sending the route update with the lowest hop count. As the first parent CH, stores its hop count, and re-broadcasts it with the hop count plus one. If the hop count of the received route update is equal to the first parent node, each node records the node sending the route update as a candidate parent node. Otherwise, no action has to be taken. Figure 6.1 shows the optional path tree. When the route setup is completed, each node has the first parent node and, if ever, multiple normal parent nodes. Each node treats the first parent node and all of the normal parent nodes equally as next-hop nodes. When the node has messages to be forwarded, it forwards each message to one of the next- hop nodes with less congestion level. 99

3 6.3 Changing Routing for Congestion Control Protocol (CRCP) CRCP is based on cognition detection technology to detect the potential congestion timely and effective. Once congestion happens inevitably, CRCP (Changing Routing for Congestion Control Protocol) is presented to reallocate traffic with altering route protocol to mitigate congestion, avoid conflict, enhances data transmission reliability of cluster head. Congestion data local storage strategy effectively avoids data lost during the congestion period and guarantees the reliability of data transmission. Therefore it is important to prevent the real-time traffic from consuming the bulk of network bandwidth and leave non-real-time data starving and thus incurring large amount of delay CRCP Algorithm Flooding algorithm using hopcount *if required* // for each cluster head(ch) node// Set candidate_nodes to 0 If current_node is base_station Set hop_count to 0 Broadcast flood_pkts with hop_count Else if current_node is CH _node which receives flood_pkts and accepting them Set current_node to hop_count+1 Send ack_pkt with current_node_id Broadcast flood_pkt with current_node_id and hop_count Ignore subsequent flood_pkts Else if current_node is CH_node receives ack_pkt Candidate_nodes +1 Directly call Congestion Detection algorithm // Call HHCC protocol// Route Changing and LDS algorithm If Current_node receives ack with congestion bit set Update candidate_parent table Search candidate_parent table Find node_id with min (congestion bit) Send data packet. If current_node receives congestion_update_msg update candidate_parent table else if current_node receives data packet and accepting them set buffer to buffer+1 if buffer=full update congestion bit send ack_pkt with congestion bit information 100

4 6.4 Simulation Parameters Parameter Value Network Size 1000 X 1000 Total Number of Nodes 200 Simulation Time 200s Transmission Range 25 m Base Station Position (250,250) Initial Energy 20 J Data Packet Size 30 Bytes Node Queue Type CMU Priqueue Transmission Range 512 kbps Table 6.1. Simulation Parameters. 6.5 Simulation Results and Discussions NS2 simulator is used to simulate the proposed protocol. In the simulation, the channel capacity of mobile hosts is set to the same value 2 Mbps. The distributed coordination function (DCF) of IEEE as the MAC layer protocol is used. Packet drop rate in the network From Figure 6.2 it is observed that CRCP reduces data rates for all sensors in response to congestion and altering routing tries to prevent congestion from being developed and therefore avoids packet drops. 101

5 Figure 6.2. Packet drop rate It sharply reduces the amount of traffic and removes the congestion more quickly than no congestion control. CRCP + LDS try to prevent congestion from being developed and therefore avoid packet drops. Source rate in the network Figure 6.3 compares the total source rates of the schemes with respect to time. During the course of congestion control/avoidance, the total source rates are reduced. Figure 6.3. Source rate 102

6 At around time 200 seconds, congestions are removed in all schemes (except for No Congestion Control) and the total source rates stabilize. Congestion Avoidance achieves the best source rate due to its capability of redirecting traffic towards other downstream paths that are not congested. Average routing distance of each packet Figure 6.4 shows that CRCP has the smallest routing distance, which means nodes closer to the base station, send much more than their fair share. The routing distance of CRCP + LDS is much closer to that of Global Rate Control, which means distant nodes are penalized much less. Figure 6.4. Average routing distance Routing delay With Figure 6.5 it is seen that the average routing delay per packet after the congestions is removed. The number of hops and per hop queuing delay mostly determines the endto-end routing delay. Backpressure fully utilizes the buffer space. Consequently the average routing delay decreases when the average routing distance decreases. 103

7 Figure 6.5. Routing Delay Simulation results show this protocol has better throughput, transmission reliability and packet delivery ratio with reduced energy consumption. 6.6 Summary In this chapter, a timely potential congestion detection technique based on cognition detection technology is developed. When the congestion happens unavoidably, CRCP is presented to reallocate traffic with changing route protocol to mitigate congestion and avoid conflict which will enhances data transmission reliability of Cluster head. Congestion data local storage strategy is effectively avoids data loss during the congestion period and guarantees the reliability of data transmission. This protocol also provides a network load balancing, postpones network system lifetime and effectively prolongs the life cycle of the clusters. In next chapter we present conclusion and future work. 104