Available online at http://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=11&IType=8 ISSN Print: 0976-6480 and ISSN Online: 0976-6499
DOI: 10.34218/IJARET.11.8.2020.061
© IAEME Publication Scopus Indexed
A PRACTICAL STUDY ON THE
PERFORMANCE METRICS OF THE
SELECTIVE PROTOCOLS IN WSN
Dr. P. AnbalaganAssistant Professor, Department of Computer Science and Engineering, Annamalai University, Annamalainagar, Tamil Nadu, India.
Dr. S. Saravanan
Assistant Professor, Department of Computer Science and Engineering, Annamalai University, Annamalainagar, Tamil Nadu, India. ABSTRACT
Wireless sensor network is a self-organized wireless network which consists of number of embedded systems like sensor, sink node and hardware components. In wireless sensor network, power consumption, energy efficiency, lifetime of the network are the major concern problems. When communication is carried out through the sensor nodes, lot of energy is drained from the network which in turn makes the falling of lifetime of the network. To improve the lifetime of the network, effective routing and scheduling process should be done in the network. To address the mentioned various researchers come up with various strategies and routing protocols. This paper performs a clear analysis of the selective protocols and gives the illustration of the analysis. The selective protocols include routing and scheduling.
Key words: WSN, IoT, Protocols, routing, energy
Cite this Article: P. Anbalagan and S. Saravanan, A Practical Study on the Performance Metrics of the Selective Protocols in WSN, International Journal of Advanced Research in Engineering and Technology, 11(8), 2020, pp. 617-628.
http://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=11&IType=8
1. INTRODUCTION
Wireless sensor network is a fastest emerging technology which composed of tiny sensor nodes, sink node. It is a self-configured network where the communication can be carried out among themselves. It consists of tiny sensor nodes which monitors the environmental conditions like pressure, humidity, vibration etc. The data from the sensor nodes are collected and pass to the sink node. From the sink node the data is transferred to the main node or the central location. At the sink node, the collected data get analyzed. The sink node or the base
station which act as conjugation between the user and the sensor network. The sensor node transmits data through radio signal. Figure 1 shows the functionality of the sensor network.
Generally, a wireless sensor node composed of sensing unit, processing unit, radio transceivers, computing devices and power components. Each individual node is resource constrained with limited power, storage capacity, bandwidth and processing speed. When the sensor nodes are deployed, they form a self-organized network where they can communicate with each other. The sensor in the network automatically begins to collect the information.
The nodes also sent the queries to the control unit to perform specific tasks or instructions or sensing the samples. The sensor nodes may work either in continuous mode or event driven. The location and positioning of the sensor node can be found by using global positioning system and local positioning system algorithm. The wireless sensor network provides a feature of adding or leaving node a network. In sensor network the sensor nodes are assembled into clusters. Each cluster is headed by cluster head. The cluster head takes all the data‟s from the nodes and transmits to the destination. Before passing the information to the destination, the cluster head removes all data redundancy. Once the data redundancy is removed, the cluster head sends the data to the destination. As the amount of data transmission increases, the cluster head draws more energy from the network.
Satellite Internet Mobile Communication Member Node Node 3 Node 1 Node 2 Node 4 Node 5 Cluster
Head BS Control Centre
Base Station
Figure 1 Sensor network functionality with connected nodes
To equalize the energy consumption in all nodes, cluster head rotation is done. While deploying sensor nodes, lot of challenges are placed. Each sensor node communicates through wireless with lossy lines. An additional challenge related to network is energy consumption and lifetime of the network. In order to save energy consumption in network, the extra
components should be on idle state during low traffic period. Wireless sensor network may works in single hop communication or multi hop communication.
The main characteristics of wireless sensor network are (i) Dynamic network topology: the network on updating automatically, when there is addition and deletion of network. (ii) application specific: the network design can be changed based on the requirement. (iii) Energy consumption: as the nodes are dynamic, energy limitation is there. (iv) Self-configurable: as the nodes are deployed, they can be self-configured to form a network. Wireless sensor networks found special application in wireless multimedia sensor networks (WMSNs) [8], wireless underground sensor network (WUNs), wireless body sensor network (WBSNs), wireless sensor-actor network (WSANs). WSNs found variety of applications including military applications, surveillance and monitoring for security and threat detection, health applications such as patient monitoring, agriculture, landslide detection, etc [8-11].
The organization of the paper is as follows: Section II exhibits the literature review of the state of the art protocols. Section III discusses the role of routing and its characteristic usage in the WSN and IoT. Section IV clearly exhibits the routing study and analysis. Section V exhibits the scheduling study and its analysis. Section VI shows the experimental setup and test bed used. Finally the paper is concluded in the Section VII.
2. LITERATURE REVIEW
Generally routing is implemented in sensor network to reduce the energy utilization of the network.
Xiang Yang et.al (2015) presented that the overview of routing protocol in wireless sensor network. However some of the key problems like QoS communication, energy efficiency, security routing protocols are need to take concern [1].
Tanvi sood et.al (2018) presented that the data packets are communicated effectively in wsn. New challenges like data get resource constraint are to be solved. Still energy conservation, network lifetime are the major drawbacks of the network. Energy efficient routing protocol should be implemented to solve these issues [2].
Neha et.al (2013) presented the design challenges in routing. The design of routing protocol is to reduce the energy utilization in the network. The main objective of routing is to maintain the sensor node operation for long time and to lengthen the network lifetime. The energy consumption of the sensor is responsible for the sending and transmitting the data [4].
Deepak goyalet.al (2012) presented the data routing approaches in the network and the classification of data routing protocol namely data centric, geographic routing, hierarchy routing. Routing protocol is designed for different applications [7].
Rachid Ennajiet.al (2009) presented the traditional routing methods in the network. Mobility of the network needs to take in concern. A Priority Based Energy Efficient Routing Method for IoT systems was developed Safara et al. IoT is the advanced technology used in wireless sensor network. By using IoT, the network can be controlled anywhere any time by using Internet technologies. In the era of IoT, data transmission between nodes and discovering the best route from node to node is the challenging issue. The management of resources is more important to achieve the optimum node collection and effective communication with each other. In IoT, traffic congestion occurs due to collection of large volume of data in the network which may be in the form of images, videos etc. In order to reduce the traffic congestion, an effective routing algorithm is implemented [5].
In PRINergy technique, each node consists of two methods (i) priority (ii) transmission rate. Each node consists of single bit either 0 or 1. Here the input data are in the form of video or image format. The highest priority (0) is given to the video data transmitting nodes whereas
the lower priority (1) is given to the image data transmitting nodes. If there is congestion in the network, the nodes with smaller data such as image, texts is given priority to transfer the data. If there is no congestion, the node with higher data like video are given priority to transfer the data. To synchronize the data between the sender and receiver and to reduce energy consumption TDMA time slots are used. To place the data in TDMA slot, the data traffic is verified first. If traffic at the nodes is high, image packets are transferred. If there is no traffic at the network, video packets are sent. Time slots are dedicated for the priorities and the transmission rate [6].
The coordinator plays a role for the time slot dedication. If multiple nodes have same precedence, TDMA selection will based on the transmission rate. To synchronize the frame, preamble bits are pre owned at the first part of the frame while sending and receiving the data bits. For example if the end user find a logical data on the channel by accepting the sample of 0101101 with no data on the channel. When the end user accepts 101011011means the preamble bits of two sequences „1‟ is added to the data. After the validation of data in the channel, the data is transferred to destination address. The source address denotes the sender address on the frame. In the destination address field, the address of the field to which the frame is needed to sent. The control part of the packet determines the length of the payload packet. The data packet confirmation is confirmed through the ACK signal sent by the control section. Payload represents the space used by the data processing unit to receive the data from the sensor node by serial communication. The size of the payload bytes varies from 0 to 32 bytes. The CRC (cyclic redundancy check) is responsible for the error checking in the frame. The error detection code is enabled to check the frame validity. If the CRC doesn‟t match, the frame is invalid.
3. ROUTING
The foremost idea for routing algorithm is used to find the best and the shorter route linking the sensor node and the sink node, from sink node to central node. The routing problem in the network leads to maximize energy utilization and reduce the network lifespan. In order increase the lifespan of network and to reduce energy consumption, routing algorithm are used.
3.1. Challenges and Design Issues for Routing In WSN
The design of routing protocol influenced by many factors. Before implementation of routing protocol these challenges should be overcome. List of the routing challenges and design issues of WSNs are
Node Deployment: node deployment in network depends on the application and the requirements. It can be either manual or random deployment. In manual method, the sensors are deployed physically and the data is scattered through the pre-established path. But in random method, the sensor nodes are placed in unplanned manner which creates an ad hoc architecture. If there is a non-uniform distribution, optimal clustering is employed which gives an energy efficient network.
Energy Consumption: sensor nodes used batteries for their power supply. When large amount of data is collected from the surroundings. The sensor nodes require more energy for their transmission. Due to large amount of data, the energy is lost. For effective communication, energy efficient network is needed. In multi hop wireless network, each node plays a role data sender and data receiver as well. If there is a power failure in the network it causes change in topology, rerouting and rescheduling of the data packets and reorganization of the network.
Data reporting Method: data reporting method can be of different ways. It may be event driven or query based or time based or hybrid method. In time driven method, all the sensor nodes sense the environment at a periodic time interval. The sensor nodes can switch on their sensors and transmitters at a periodic time to sense the environment and transfer the data to the base station periodically. In event and query-based method, the sensor nodes will sense the sudden and drastic changes that happen in the network or a query is raised from the base station. These methods are suitable for the time critical applications.
Fault Tolerance: Due to lack of power, physical damage or environmental interference, sensor node may fail. If the sensor node fails it won‟t affect the overall task in the network. If multiple nodes fail, the MAC layer and the routing protocol should find different way to reach the base station and from base station to the final node. More energy is needed to rerouting of data packets. Data redundancy is checked at each node.
Data Aggregation: The data collected from the sensor node is checked for data redundancy, to remove redundancy in data, similar data should be aggregated. Data aggregation is the collection of data and converted into similar form. This technique improves the data accuracy and network lifetime.
Quality of Service: In some applications, the sensed data in the network should reach the destination in certain period of time. In many applications energy conservation is directly related to network lifespan, quality of data is not considered. As the energy gets reduced, the quality of data gets delayed and network lifetime is conserved [9].
3.2. Routing Protocol in WSNs
In wireless sensor network, routing protocol can be classified into three types namely data centric routing, geographic based routing and hierarchy based routing based on the network infrastructure. Based on the protocol operation it can be classified into negotiation based routing, multi path based routing, query based routing, QoS based routing and coherent based routing.
Data Centric routing: In data centric routing the sensors are deployed randomly. The information on the sensor node is collected, it doesn‟t check which sensor node get sensed. In data centric protocol the node gathers the data event; the data gets forwarded to the base node whose responsibility is keeping the data set preferably than keeping the data itself or forward to the external storage accordingly. Once the node get acknowledgement from any of the events, it gets the data from the respective node [12 – 13].
Sensor protocol for information via Negotiation (SPIN):SPIN is a freshly routing protocol in data centric routing. In SPIN protocol it consists of four protocols namely SPIN-PP, SPIN-BC, SPIN-RL, SPIN-EC and modified SPIN. In SPIN protocol, when a specific event occurs, the network was divided into two regions. Sensor node on first region and sensor and sink nodes on second region [14]. When receiving the data from event node, the sensor node from the first region unwantedly waste their energy in sending and receiving the data. The data have to travel more nodes in order to reach the sink node. When an event occurs during the transfer of data through the nodes in the second region. In this method effective energy transmission not occurs. Therefore for an effective energy consumption modified SPIN or M-SPIN protocol is used. In M-SPIN protocol, there are three phases (i) discovery phase (ii) negotiation (iii) data transmission. In discovery phase, the distance between the source node to the sink node is called hop distance. In negotiation phase, the actual data is transmitted by the hop distance. In data transmission phase, the data is transmitted from the source node to the sink node [15].
Rumor routing (RR): In rumor routing the protocol consists of two messages namely agent message and query message. The source node sends the agent message randomly
throughout the network and the sink node send the query message to the source node. When the agent message and the query message of the route are cross each other. There is an amalgamation between the source node and sink node. In this process, the rout of sensor nodes and sink nodes are chosen randomly, this causes loop path in data transmission which causes loss in power and reduced lifetime [16].
Geographic routing protocol: In geographic routing, the process is based on the location and the positioning of sensor nodes. The routes of the nodes are established by the geographic location of the sensor node. The nodes can communicate with each other. The position of the nodes can be calculated using localization algorithm [17]. Each node in the network communicates to the neighboring node. While forwarding the data packets, the node chooses the following node followed by it‟s neighbor and target nodes based on the location. The nodes can transfer the data till the data in the neighboring data. In this method, only a part of the network is in active mode while sending or receiving the data. In this process energy is saved [18].
Geographic Adaptive fidelity (GAF): In this method, the entire network was divided into equal virtual grid pattern. There is only one active node which transmits the data through the grids, where the other nodes are in inactive mode [21]. The other nodes in inactive mode periodically awaken and inform the status whether it is working or not. From this view, the lifespan of the network is prolonged. The position of nodes is located by GPS. This method is not suitable when coming to energy awareness [20].
Geographical and energy aware routing (GEAR): In GEAR, the sink node sends query message to all the source nodes in the network. In wireless sensor network, the query message is classified into two propagation, in first propagation; the sink node utilizes the geological unicast address to send the acknowledgement request to reach the source node. In second propagation, once the acknowledgement request reaches the target node, then it further spread the queries to the target node by iterative geographic flooding [21 - 23].
Geographic Random Forwarding (GERAF): This protocol consists of two wireless transceivers. The nodes are active only in a certain periodic time or a unplanned periodic sleep or detain in the main channel. When the communication begins in the network, only the node which wants to send and transmit the message will be active to send the control message to the main location. It uses a cut-throat approach to selects the readdressing hops. It gives an absolute solution in selecting the readdressing nodes by hop distance which results in reducing the number of data readdressing hops. The GERAF protocol defines the readdressed area and divides the region into precedence sub regions. The sensor node sends the request to send signal to each region according to the region‟s priority from high to low, it looks for the readdressing node to start the transmission. It provides clear idea for the forwarding node and clear to send signal. This method is not an energy efficient process [24].
Hierarchy routing protocol: In hierarchical routing, more energy will be related to the cluster head and low energy will be related to the cluster node. The cluster head will transfer the data to the base station and the cluster node will gather the information and transfer to the cluster head. In this method energy consumption is decreased effectively [25].
Low Energy Adaptive Cost Hierarchy (LEACH): It is a low energy consumption adaptive clustering protocol. In this protocol, it has two stages namely cluster structure evolution and steady formation. In cluster structure evolution, all the nodes are assigned into clusters; each cluster selects its cluster head. Once the cluster head formation is done, it takes the lead of CSMA-MAC to broadcast the ADV [26].
Threshold Sensitive Energy Efficient Sensor Network (TEEN): In TEEN, the cluster node through the base station transfers the data on election of the cluster head and broadcast
the hard threshold and soft threshold. This method is not suitable for the periodic collection system [27].
Power Efficient Gathering in Sensor Information Systems (PEGASIS): it is the most effective approach compared to LEACH protocol. In LEACH protocol, there is group of cluster formation in the network. Apart from forming cluster heads PEGASIS forms chain formation from the sensor nodes. In chain formation each node is selected to send and receive the data. Only the transmitting node and the neighbor node will be in active mode from the chain for transmitting the data. The data transmission will move from node to node. When the transmission ends at the base station, the next round starts. In PEGASIS the node finds its neighbor node by its signal strength so that the two nodes will be active mode. From this the power requirement is reduced [28].
3.3. Scheduling Algorithms in WSNs
Scheduling can be defined as the process of allocating resources to the tasks based on objectives. Scheduling in WSN is resource constraint. Effective scheduling process reduces the data collision in the network. Scheduling requires the following phases (i) finding the resources (ii) clarifying of resources (iii) selection of the resources from filters (iv) selection of scheduling protocol for the resources.
Scheduling Techniques
The following scheduling techniques are used in WSNs:
First Come First Serve: FCFS is the basic method in scheduling process. In this process, the data packets are processed as per the time as it reaches the buffer. The data packet which reaches the destination will be processed without any priority or preference. Similarly, the other data packets will be processed at the time sequence. So it takes longer time to finish the sequence [30].
Earliest Deadline First: In EDF, the data packet with the earlies deadline priority is processed. The received data packets will scheduled as per due data by the scheduler. The packets received are placed in the order of their deadlines. Since the priorities of the tasks are scheduled, the priorities are reassigned dynamically at the time. It is a kind of dynamic real time scheduling [31].
Priority based scheduling: In priority - based scheduling, the data packets with high priority is scheduled and processed first at the base station. Priority scheduling can be classified into (i) pre-emptive scheduling and (ii) non pre-emptive scheduling.
Pre-emptive scheduling: in this method, the task with higher priority is scheduled first than the task with lowest priority. The higher priority task is processed first. Non Pre-emptive scheduling: this type of scheduling does not allow the highest priority task to jump out of the queue to get executed at earlier [31].
Single queue scheduling: in this scheduling, only one queue is placed in the sensor node. Once the data enters the single queue, it enters into the buffer and sorted according to the packet size, priority etc., [31].
Multi -level queue scheduling scheme: In multi- level queue, there is two or more number of queues in the sensor node. The data packets are placed according to the burst time and they moved to the different queues based on the priorities [32].
Shortest Job First Scheduling Scheme: In SJF scheduling, the data packets are scheduled out of the queue through the shortest execution time. In this scheduling scheme, the data packet with less execution time is processed than the data with high execution time.
Higher packets are given lowest priority. This method leads to starvation of the longest data packets [29].
Ant Colony Algorithm (ACA): Ant colony algorithm takes a inspiration from the scout nature of ants. ACT provides the optimal solution for the combinatorial optimization. It is used to find the least route form source node to the base station. During the scouting process, the ants locate the food source. They leave their trail on the path. This allows the other ants to find the trail of essence and level of essence for finding the path to the food source. Similar to this method, the shortest path is found for the transmission of data [10].
Bee Inspired Algorithm: this routing algorithm is persuaded from the behavior of honey bees. In honey bees nectar, a single queen is responsible for the collection of honey. In MBO (Marriage in Honey Bee Optimization) the algorithm begins with the single queen with no family. In this algorithm, it develops a colony with the family with two or more queens. Some of the bee algorithm foraging the behavior of the bees such as Bee Colony, Artificial Bee Colony, The Bee Algorithm [10].
TDMA Scheduling Scheme: In wireless sensor network, the channel access can be done in random manner or scheduling process. In random method, the performance of the network degraded due to data collision. For collision free network, an efficient TDMA scheduling method is used. The nodes are assigned specific time slot which allocated from the centralized nodes or from the destination. Each time slot can assign to accommodate a single data packet for transmitting and receiving the data. By assigning a time slots, data collision avoidance can be done. By making the transceiver sleep, the network lifetime also improved [33].
Genetic Algorithm (GA): The critical aspect of multi cluster environment is the allocation of resources to the network. To solve this problem, genetic algorithm is used. These algorithms are based on the initialization, crossover, mutation are used to solve key problems like crossover probability, mutation probability, and fitness function. This algorithm ends only when the output is satisfied so it takes longer time than the other scheduling algorithms. A novel genetic algorithm was developed to produce the optimum solution for the task scheduling [34].
4. EXPERIMENTAL SETUP AND RESULTS
The proposed algorithm is successfully experimented in a self-developed simulated environment as shown in Figure 2. The entire simulation tool is built using Python 3.7. The entire experimentation is carried with the sensor nodes of dissimilar type of both homogeneous and heterogeneous with the count upto 200. Further, the simulation scenario is carried out for two cases, i) Normal WSN with the stable network, ii) Normal WSN with the instable network Various validations such as node failure, jitter, node reformation rate estimation etc., are carried and monitored. To prove the efficacy of the proposed algorithm the resource monitoring is carried out for the first two scenarios. The entire setup is utilized to execute all the state of art algorithms. The performance metrics are also monitored and detailed in the results section.
Figure 2 and Figure 3 shows the performance metrics of the selective routing and scheduling protocols. From the results it could be inferred that the LEACH protocol stands top in WSN deployment in terms of jitter, accuracy, throughput etc. For scheduling, the genetic algorithm based approaches are optimal and effective.
Figure 2 Performance metrics of routing protocol
Figure 3 Performance metrics of scheduling protocol
5. CONCLUSION
This paper is concluded by presenting the state of art review on the WSN and IoT routing and scheduling protocols. From the literature it is clear that the existing routing protocols utilizing the clustering approaches are optimal and well-being in all the environment. Further, this paper also gives the clear illustration about the scheduling among the sensor nodes within the network. This also helps to understand the WSN and IoT clearly. This paper also presents the practical difficulties of the WSN network design and deployment. Finally, the paper gives the clear insight about the selective protocols such as routing and scheduling.
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