A Stateless Protocol For Real Time Communication

Published Date: 02 Nov 2017

The proposed ECMR protocol combines the concept of clustering and multipath routing .Efficient utilization of energy resources and minimizing the delay in the network is the main goal of the protocol, it also increases the other performance metrics like packet delivery ratio and throughput. These performance metrics (i.e. delay, throughput, PDR) are referred to as Quality of Service(QoS) requirements sensor networks requires energy and QoS awareness in different layers of protocol stack in order to have efficient use of the network resources and effective access to sensor values. Thus QoS routing is important, multipath routing which focus on the QoS parameters, it also has the following benefits,

Load Balancing:

It is achieved by dividing the traffic across multiple paths. This method of routing is applicable to wireless sensor networks. It spread the energy to all nodes so potentially resulting in longer lifetime. It also avoids congestion and bottle-neck problems.

Reliability and fault tolerance:

Reliability here refers to the probability that the destination received the intended rate of packet. It is an important factor WSN, because packet loss, interference, media access conflicts, network topology not constant etc. They affect the transmitted wireless signals.

Failure protection and increase resiliency to route failures is one of the reason for multipath routing. Multipath path between source and destination are discovered, when one path fails, the alternative path will be used. It can be also used simultaneously for data routing.

Aggregated Bandwidth:

Single-path routing provides less bandwidth compared to multipath technique, with multipath direction the overall bandwidth increases.

Minimizing end-to-end delay:

Path between source and destination are considered as disjoint, so the correlation/collision is very less, no route coupling between routes, the delay is minimized. The data is divided into segments and sent to the destination through multipath paths.

The main aim of cluster based routing is to efficiently maintain the energy consumption of sensor nodes; it also describes load balancing and resource utilization, aggregation. The clusters are formed through location-based clustering technique. The cluster head is selected with basis of distance and the residual energy. The shortest path between the sink and cluster head is calculated and alternate path is sorted based on the delay constant. With various simulation time and number of nodes the QoS metrics values are calculated.

CHAPTER-2

LITERATURE SURVEY

CLUSTER BASED QOS AWARE ROUTING PROTOCOL

K. Akkaya and M. Younis [ ] proposed a cluster based QoS aware routing protocol that employs a queuing model to supervise both real-time and non-real-time traffic. The protocol considers only the end-to-end delay. The protocol associates a cost function with each link and uses the K-least-cost path algorithm to find a set of the best candidate routes. Each of the routes is checked against the end-to-end constraints and the route that satisfies the constraints is chosen to send the data to the sink. All nodes initially are assigned the same bandwidth ratio which makes constraints on other nodes which require higher bandwidth ratio. Furthermore, the transmission delay is not considered in the estimation of the end-to-end delay, which sometimes results in selecting routes that do not meet the required end-to-end delay.

A STATELESS PROTOCOL FOR REAL-TIME COMMUNICATION

IN SENSOR NETWORKS (SPEED)

SPEED [12] is another QoS based routing protocol that provides both soft real-time end-to-end services. Each sensor node maintains information about its neighbours and exploits geographic forwarding to find the paths. To ensure packet delivery within the required time limits, SPEED enables the application to compute the end-to-end delay from the speed of packet delivery by dividing the distance to the sink before making any admission decision. Furthermore, SPEED can afford congestion avoidance if the network is congested. However, while simulation results in [12] have shown that SPEED outperforms other protocols, this does not mean that SPEED is an energy efficient protocol. Because the protocols used in the head to head comparison are not energy aware protocols. The SPEED protocol does not consider any energy metric in its routing protocol, which makes a question about its energy efficiency. Therefore, to understand SPEED's energy consumption and usage, it should be compared with energy aware routing protocols.

MESSAGE-INITIATED CONSTRAINED-BASED ROUTING

Message-initiated Constrained-Based Routing (MCBR) mechanism is proposed in [10]. MCBR is composed of explicit specifications of constraint-based destinations, route constraints and QoS requirements for messages, and a set of QoS aware meta-strategies. Given the destination and routing constraints, routes from the source to the destination are established through flooding the network. Through applying general purpose meta routing strategies, a data message is routed from source to destination via a route that satisfies the QoS requirements for that data message. However, the extra control packets (because of flooding the network with control packets) are a significant overhead. The same authors in [19] have proposed the QoS aware learning based routing to decrease the complexity of MCBR protocol and enhance its performance.

MULTICONSTRAINED QOS MULTI-PATH ROUTING (MCMP)

PROTOCOL

Recently, X. Huang and Y. Fang have proposed a multi-constrained QoS multi-path routing (MCMP) protocol [14] that uses braided routes to deliver packets to the sink node according to certain QoS requirements expressed in terms of reliability and delay. The problem of the end-to-end delay is formulated as an optimization problem, and then an algorithm based on linear integer programming is applied to solve the problem. The protocol objective is to utilize the multiple paths to augment network performance with moderate energy cost. However, the protocol always routes the information over the path that includes minimum number of hops to satisfy the required QoS, which leads in some cases to more energy consumption.

DENSED CLUSTER GATEWAY BASED ROUTING (DCG)

DCG is a technique used to determine clusters for ad hoc mobile networks using the k-tree core approach. Connectivity between nodes are determined by the wireless range of broadcast signal. First, a distributed spanning tree, which is the sub graph of the network topology, is constructed and the root is selected towards the centre of the network as possible. During the construction, the edges of the trees are monitored and tracked. These edges are categorized by colours- yellow edges and green edges. The use of colour attribute in DCG determines the role of the edge on the tree formed. Cluster heads and gateways are used as special nodes which have added responsibilities over the ordinary participating nodes in the network. A cluster head keeps track of the entire member (nodes) in a cluster, and the routing information needed. The gateways are the nodes at the border or edge of a cluster and communicate with the gateways of neighbouring clusters.

ASSOCIATIVITY BASED CLUSTERING (ABC)

Associativity Based Clustering (ABC) is a strategy proposed using the ABR protocol as its base to support location based routing protocol. ABC presents framework for dynamically organizing mobile nodes and electing a dominating set in a highly spontaneous large scale mobile ad hoc networks. A node is selected as the clusterhead based on nodes having Associativity states that imply periods of spatial, temporal and stability. The results of simulation show that it is more dynamic, distributed and adaptive. A cluster head as elected based on spatial associativeness and based on the notion of virtual clusters. The location information maybe then obtained using Global Positioning Systems (GPS) or other self positioning algorithms. Existing solutions to this problem are based on the heuristic (mostly greedy) approaches and none attempts to retain topology of the network

MULTIPATH-DSR

Multipath-DSR (M-DSR) [ ] is a simple multipath extension of the popular DSR, in which alternate routes are maintained so that they can be utilized when the primary one fails. Instead of replying only to the first received RREQ as DSR, the destination node sends an additional RREP for a RREQ which carries a link disjoint route compared with the routes already replied. However, M-DSR can’t compute link disjoint paths in many cases because the intermediate nodes drop every duplicate RREQ that may comprise another link disjoint path.

AN ENHANCED CLUSTER-BASED MULTI-HOP MULTIPATH ROUTING PROTOCOL

CBMMRP distributes traffic among diverse multiple paths to avoid congestion, optimize bandwidth using and improve the sharing rate of channel. It uses clustering’s hierarchical structure diverse to decrease routing control overhead and improve the networks scalability. It can balance the network load, dynamically deal with the changes of network topology and improve reliability. These benefits make it appear to be an ideal routing approach for MANETs. However, these benefits are not easily explored because the data packet that is fragmented into smaller blocks must be reassembled at the destination node, it maybe lead to error and increase control overhead.

SIMPLE ENERGY EFFICIENT ROUTING (SEER)

Gerhard P. Hancke et al [16] proposed simple energy efficient routing (SEER), a novel routing protocol for wireless sensor networks intended to optimize network lifetime. SEER uses a flat network structure for scalability and source initiated communication, along with event-driven reporting to reduce the number of message transmissions. Routing decisions are based on the distance to the base station as well as on remaining battery energy levels of nodes on the path towards the base station. SEER minimizes the number of messages that are sent through the network and thus reduces the overall energy consumption.

MISENSE HIERARCHICAL CLUSTER BASED ROUTING

ALGORITHM (MICRA)

Kavi K. Khedo et al [ ] proposed the MiSense hierarchical cluster based routing algorithm (MiCRA) to extend the lifetime of sensor networks and to maintain a balanced energy consumption of nodes. MiCRA is an extension of the HEED algorithm with two levels of cluster heads. In MiCRA cluster heads are randomly selected based on their residual energy and nodes join clusters such that communication cost is minimized. This approach can be applied to the design of several types of sensor network protocols that require energy efficiency, scalability, prolonged network lifetime, and load balancing.

CONTEXT AWARE CLUSTERING HIERARCHY (CACH)

Md Enamul Haque et al [19] proposed an energy efficient routing protocol, Context Aware Clustering Hierarchy (CACH) where cluster formation is entirely based on the context of the environment. Moreover, an efficient technique has been utilized to avoid similar data traffic across the network and cluster head role has been equally distributed among the nodes. In future, the protocol will include the implementation of multi-hop communication between the cluster head and the base station, which can contribute more in energy efficiency. The super clustering technique which is efficient method for large number of sensor nodes will also be included.

ENERGY CONSTRAINED MULTIPATH (ECMP) MODEL

Antoine B. Bagula et al [ ] proposed the energy-constrained multi-path routing in wireless sensor network (ECMP). The main idea driving the ECMP model is that in the content of wireless sensor networks, efficient resource usage should reflect not only efficient bandwidth utilization but also a minimal usage of energy in its strict term. While, the MCMP model routes the information over a minimum number of hops, the strength of the ECMP model lies in the fact that it trades between minimum number of hops and minimum energy by selecting a path with minimum number of hops only when it is the path with minimum energy or a longer path with minimum energy satisfying the constraints.

Energy efficient and QoS based routing protocol (EQSR)

EQSR [ ] protocol is energy efficient and quality of service aware multi-path routing protocol designed specifically for wireless sensor networks to provide service differentiation by giving real-time traffic absolute preferential treatment over the non-real-time traffic. Our protocol uses the multi-path paradigm together with a Forward Error Correction (FEC) technique to recover from node failures without invoking network-wide flooding for path-discovery. This feature is very important in sensor networks since flooding consumes energy and consequently reduces the network lifetime. EQSR protocol uses the residual energy, node available buffer size, and signal-to-noise ratio to predict the next hop through the paths construction phase. EQSR splits up the transmitted message into a number of segments of equal size, adds correction codes, and then transmits it over multiple paths simultaneously to increase the probability that an essential portion of the packet is received at the destination without incurring excessive delay. EQSR protocol handles both real time and non real-time traffic efficiently, by employing a queuing model that provides service differentiation. But it does not concentrate on the impact of the network size, path length, and buffer size on the performance metrics.

CLUSTER BASED MULTIPATH ROUTING PROTOCOL

Cluster based multi path routing protocol for energy conservation in wireless sensor networks. It includes three phases such as cluster construction, inter-cluster multipath route establishment, cluster reconstruction and alternate path selection. In cluster construction phase, cluster heads are selected based on the distance and residual energy level of the sensor nodes. In multi path route establishment phase, multiple shortest paths are determined between each cluster head and the sink by using some intermediate gateway nodes. The paths are sorted based on the energy level and hop count. The gateway nodes can be rotated for each cycle, randomly. In cluster reconstruction phase, if the Cluster Head’s (CH) residual energy is below some threshold, it will select another node with maximum residual energy in this cluster to take over. When some of the sensors in the primary path have dissipated too much energy, we select the alternative path to connect to the sink. By simulation results, we have shown that the proposed approach achieves better throughput, packet delivery ratio with reduced energy consumption and delay.

CLUSTERING BASED MULTIPATH ROUTING

ALGORITHM (CMQ)

CMQ is a clustering based routing algorithm that uses a new cluster head selection algorithm and also performs path discovery using multiple criteria such as remaining energy, number of neighbours, and probability of successfully packet sending and link quality. Cluster head selection phase is almost like a cluster head selection algorithm in HEED but the difference is that in the beginning, all nodes calculates the probability of cluster head selection. It has 3 phases Path Discovery, Path Maintenance, Path Selection.

CHAPTER-3

PROBLEM STATEMENT AND ITS SOLUTION

EXISTING SYSTEM

In wireless sensor networks, the protocols with minimum energy path divest the node energy quickly and time taken to determine the alternate path increases. Single path routing increases the network delay and the system lifetime. The existing routing protocols in networks increases the node delay. However, determining worst-case bounds has limited applicability in WSNs for three reasons: First, because of the randomness in wireless communication and the low power nature of the communication links, worst-case bounds do not exist in most practical scenarios. Second, the large variance in the end-to-end delay in WSNs results in loose bounds that cannot accurately characterize the delay distribution. Finally, most applications tolerate packet loss for a lower delay of higher priority packets since the efficiency of the system is improved.

Drawbacks of the existing work:

Worst Case Performance Bounds:

The drawbacks of worst case performance bounds are analysed by the author, they have limitations over the WSN’s due to the randomness in wireless communication and low power nature of the communication links. The large variance in the end-to-end delay of WSN does not allow to characterize the delay distribution in worst-case analysis. The next drawback is the packet loss in the lower delay of higher priority of packets. So it is not applicable to most practical WSN’s applications.

MAC protocols

The delay distribution of MAC protocols has been analysed in the related work, most of the protocols has been investigated including IEEE 802.11b DCF protocol, IEEE 802.15.4 and TDMA protocols. All these protocols focus on the broadcast network where saturated traffic is considered. Hidden node problems and low traffic rate of WSN’s cannot be captured by these protocols.

Data aggregation

The end-to-end delay probability and network lifetime analysis is given for WSN which perform data aggregation, but with the assumption that the packet transmission is exponentially distributed. This assumption is inaccurate for most of the MAC protocol.

PROPOSED SYSTEM

In the proposed system we have implemented the AOMDV protocol for multipath routing. The core of the AOMDV protocol lies in ensuring that multiple paths discovered are loop-free and disjoint, and in efficiently finding such paths using a flood-based route discovery. AOMDV route update rules, applied locally at each node, play a key role in maintaining loop-freedom and disjointness properties. In the network creation the clusters are formed and the cluster head is chosen on the energy basis. The neighbour node is discovered. After the cluster head is chosen the route discovery is done and the packets are forwarded. While the packets are forwarded if there is any link failure means the packet take sthe alternate route to sink. Then the performance evaluation is carried out. AOMDV shares several characteristics with AODV. It is based on the distance vector concept and uses hop-by-hop routing approach. Moreover, AOMDV also find routes on demand using a route discovery procedure. The main difference lies in the number of routes found in each route discovery. In AOMDV, RREQ propagation from the source towards the destination establishes multiple reverse paths both at intermediate nodes as well as the destination. Multiple RREPs traverse these reverse paths back to form multiple forward paths to the destination at the source and intermediate nodes.

Fig 1.2 Proposed system

CHAPTER-6

IMPLEMENTATION

DESCRIPTION OF MODULES

Simulated Architecture with random deployment of nodes with energy model

All the nodes are randomly distributed in simulated area of about 1000m x 1000m .The node size, position, and colours are initialized in the network. The simulated area and the entire data transfer can be viewed through network animator.

At start, the initial energy for all nodes are equal. All nodes are aware of their position, so they can able to control their energy consumption. The idle time and sleeping time of nodes can be specified around the simulated area of connections during transmissions.

Comparison of routing protocols

The performance of two reactive and one proactive routing protocol AODV (Ad-Hoc On-Demand Distance Vector Routing), DSR (Dynamic Source Routing) and DSDV (Destination Sequenced Distance Vector Routing) protocols are evaluated. Table below shows the values of routing protocols with performance metrics.

Nodes

AODV

DSDV

DSR

Energy

Delay

Overhead

Energy

Delay

Overhead

Energy

Delay

Overhead

5

41.008

20.44

15

480.31

20.46

35

39.220

20.48

8

10

76.462

20.40

26

87.025

20.50

61

87.348

20.42

10

20

153.57

20.41

56

173.55

20.51

116

183.79

20.44

17

50

384.12

20.39

146

464.54

20.52

270

473.63

20.41

50

70

535.86

20.42

206

637.88

20.52

401

667.07

20.44

118

Table 6.1 simulation factors

Algorithm:

src is source node

dest is destination node

N(e) Node energy

tx transmit power

rx receive power

dist(src) is the minimum distance src from dest

dist(dest) is the destination distance from src

Set up phase:

Nodes are deployed, initialized with energy.

Configuration phase:

Nodes initial energy is set during packet transmission, the transmit power is reduced from node energy.

N(e)=N(e)-tx

For data routing 3 algorithm are used in switch case

Case 1: AODV ( ) the RREQ is forwarded to the destination from source and new route is updated in the table.

Case 2: DSDV ( ) similar to the Bellman-Ford algorithm, calculates the distance with the weight of the , if it is low updated to the table, repeated until all the paths are traversed.

Case 3: DSR ( ) it uses 2 parts route discovery with RREQ and RREP, to discover a new route, update in the table. Route maintenance ( ), the route are cached until it is changed or any failure.

During receive packets, the receive power is reduced from node energy

N(e)=N(e)-rx

Determination phase:

Calculating the values for delay and overhead.

Pseudo code:

Initialization

deploy the nodes randomly

Configuring energy level of nodes

repeat until N(E)=Null

Send packet from src to dest

N(e)=N(e)-tx

Case of protocol

Aodv( ): Send RREQ,add new route in routing table

Receive RREP,add new route in routing table

Update table

Dsdv(): calculate the distance

dis(dest)=dis(src)+weight

Update table

Dsr( ): Route discovery ( )

Send RREQ,add new route in routing table

Receive RREP,add new route in routing table

Update table

Route maintenance ( )

Receive packets from dest to src

N(e)=N(e)-rx

Determine the delay and overhead

Cluster formation and cluster head selection

Here the nodes are arranged in the cluster form by location based clustering. Each cluster is assigned with the cluster head. Cluster heads are elected by the distance from the sink in the iteration and then in next iteration by nodes residual energy.

Data forwarding

Packets are forwarded to the sink through the cluster head. Packets can also sent to the nearby cluster with the gateway nodes. If any node fails or buffer size is full alternate path taken by the packets.

Alternate route selection and data forwarding

For data packet forwarding at a node having multiple paths to a destination, if the node energy depletes or the queue overloads, then switch to an alternate path; paths are selected through delay cost and shortest to the sink. AOMDV protocol is used for multipath routing where multipath possible routes are selected during initialization itself, so it reduces the delay. There are other alternatives for data packet forwarding which concurrently use all paths.

AOMDV

Ad-hoc On-demand Multipath Distance Vector Routing (AOMDV) [ ] protocol is an extension to the AODV protocol for computing multiple loop-free and link disjoint paths [ ]. The routing entries for each destination contain a list of the next-hops along with the corresponding hop counts. All the next hops have the same sequence number. This helps in keeping track of a route. For each destination, a node maintains the advertised hop count, which is defined as the maximum hop count for all the paths, which is used for sending route advertisements of the destination. Each duplicate route advertisement received by a node defines an alternate path to the destination. Loop freedom is assured for a node by accepting alternate paths to destination if it has a less hop count than the advertised hop count for that destination. Because the maximum hop count is used, the advertised hop count therefore does not change for the same sequence number [ ]. When a route advertisement is received for a destination with a greater sequence number, the next-hop list and the advertised hop count are reinitialized. AOMDV can be used to find node-disjoint or link-disjoint routes. To find node-disjoint routes, each node does not immediately reject duplicate RREQs. Each RREQs arriving via a different neighbor of the source defines a node-disjoint path. This is because nodes cannot be broadcast duplicate RREQs, so any two RREQs arriving at an intermediate node via a different neighbor of the source could not have traversed the same node. In an attempt to get multiple link-disjoint routes, the destination replies to duplicate RREQs, the destination only replies to RREQs arriving via unique neighbors. After the first hop, the RREPs follow the reverse paths, which are node disjoint and thus link-disjoint. The trajectories of each RREP may intersect at an intermediate node, but each takes a different reverse path to the source to ensure link disjointness []. The advantage of using AOMDV is that it allows intermediate nodes to reply to RREQs, while still selecting disjoint paths. But, AOMDV has more message overheads during route discovery due to increased flooding and since it is a multipath routing protocol, the destination replies to the multiple RREQs those results are in longer overhead.

DELAY COST

The route cutoff problem prevents the discovery of all disjoint reverse paths. This in turn would severely limit the number of disjoint forward paths found at the source if the destination sends RREPs only along disjoint reverse paths. Therefore, we let the destination send back a RREP along each loop-free reverse path even though it is not disjoint with previously established reverse paths. Such additional RREPs alleviate the route cutoff problem and increase the possibility of finding more disjoint forward paths.

Performance Evaluation

Simulation result illustrates the efficiency of the proposed system compared to algorithm developed for static sensor network. Finally we compare the performance of the existing & the proposed system.

Packet Delivery Ratio (PDR):

PDR also known as the ratio of the data packets delivered to the destinations to those generated by the CBR sources. The PDR shows how successful a protocol performs delivering packets from source to destination. The higher for the value give you the better results.

PDR=

Average End to End Delay:

Average End to End delay is the average time taken by a data packet to reach from source node to destination node. First we have calculated total delay by subtracting the time when packets was sent from the time when the packet was received. Then find the ratio of total delay to the number of packets received.

Delay =

Throughput:

Throughput is the ratio of total number of delivered or received data packets to the total duration of simulation time. Like, we start the packet sending at time 0.1 and finish at time 100 so total duration of simulation is 99.9 (100-0.1). This is calculated by calculating total number of received packets divided by 99.9 (simulation time).

Throughput=

Normalized Protocol Overhead/ Routing Load:

Routing Load is the ratio of total number of the routing packets to the total number of received data packets at destination. First we calculated total routing packets (RTR) then we have divided this total number of RTR by total data packets received at destination.

Overhead = ∑ RTR pkt / ∑ Recv pkt