Energy Efficient Cluster Formation Techniques

The Hierarchical Power Aware Routing (HPAR) is a power aware routing protocol that divides the network into a group of sensors called zones [12]. In this, the cluster zones are formatted, then the decision is made that how message is routed so the battery life can be maximized. This protocol provides an approximation algorithm called max-min ZPmin algorithm. In this algorithm by applying Dijkshtra algorithm the path who consumes less power is found. Then the second path is found that maximizes the minimal residual power. The advantage is that it provides both transmission power and maximizes battery

In this section, we present the details of proposed protocol. Our protocol implements the idea of probabilities for cluster heads selection based on initial energy and residual energy of sensor nodes as well as the average energy of the sensor network.

A group of wireless sensor nodes (devices) dynamically constructs a temporary network without the exercise of any pre-existing network infrastructure or centralized administration. The main goal of ad-hoc networking is multihop broadcasting in which packets are transferred from source node to destination node through the intermediate nodes (hops). The main function of multi hop WSN is to enable communication between two terminal devices through a bit of middle nodes, which are transferring information from one level to another level. On the foundation of network connectivity, it dynamically gets to determine that which nodes should get included in routing, each node involved in routing transmit the data to further

A WSN is a type of wireless networks that consists of collection sensor nodes which are tiny devices. Each sensor node of the network has different processing capability. It may contain multiple types of memory (program, data and flash memories), have a RF transceiver, have a power source (e.g., batteries and solar cells), and accommodate various sensors and actuators. The nodes communicate wirelessly and often self-organize after being deployed in an ad hoc fashion [13, 14]. Optimum need of each sensor node is to maximize its own utility function. Also the whole network requires resource assignments balance to perform in a useful and efficient way. This chapter presents a brief survey on WSNs showing its types, characterizing features, protocols and applications.

The mobile computing technology is an emerging technology, which consist of wireless sensor networks. The wireless sensor is the smallest unit of a network and some of the features supports large scale deployment, mobility, reliability and other applications. According to (Hoon-Jae, 2011), the main goals of WSNs are to deploy a number sensor devices over an unattended area and transmit to certain locations.

Wireless sensor networks are often referred to as self-adaptable or self-organizing and self-mending or self-healing networks. The self-organizing property of the network facilitates for a node to join the network without any intervention automatically. The nodes in a network can reconstruct their link organizations and can form an alternative paths whenever a node in that link fails or gets damaged. The implementation of these two properties are very precise to the network topology and the network characteristics like scalability, cost, performance and various other issues are decided by the implementation capability of the properties. The sensor nodes in the wireless sensor networks does not require any engineering and are easily deployable. The sensor nodes often with multi hop connections are responsible for

Power efficiency is the first factor that directly affects the performance of the nodes and hence of the overall sensor network. For better and desired performance, the nodes of a WSN must be efficient in terms of power which in simple words means that the duty cycle of the nodes must be made small [5]. The design considerations must take into account the sleeping mode of the nodes when there is no activity thereby reducing power consumption and contributing to performance enhancement. However, the sleep mode of nodes has the main disadvantage that if any of the nodes remains in the sleep mode for a significant chunk of time, it is likely that communication with neighbors nodes may come to a halt. Also, a reduced duty cycle for the network nodes leads to threatening the network reliability. The data as well as the control packets that maintain the routing and communication among the nodes of the sensor network will also have a delayed reception.

Abstract: LEACH TDMA schedules of each cluster are built independently. This can lead to collisions among clusters if the same channel is allotted to more than one overlapping clusters at the same time. To reduce this type of interference, in LEACH each cluster communicates using different CDMA codes. Thus, when a node is elected as CH, it chooses randomly from a list of spreading codes and informs all the nodes in the cluster to transmit using this spreading code. Hence all clusters can have intra-cluster communication in parallel. However, in large WSNs, as number of clusters increases self-noise generated by these codes may cross threshold limit and reach capacity limit. This forces to look at multiple channel use for improved throughput and energy-efficiency. We present an energy-efficient multi-channel routing protocol (CFCA) for wireless sensor networks. By computing the size of each cluster and identifying non-overlapping clusters, the proposed method allows channel reuse within WSN. This algorithm optimizes number of channels required for the given WSN.

Abstract: We analyze the wireless sensor networks protocols and present a classification and comparison of routing protocols. Several routing protocols have been projected to maximize the sensor networks life span. Nevertheless, most of these solutions attempt to determine an energy efficient path and don’t account for energy consumption balancing in sensor network. This frequently leads to network partitioning. The aim of this paper is to evaluate, analyze and compare three routing protocols (LEACH, CBR and MBC) that balance energy consumption, through a mathematical model and simulations. This paper will present a performance comparison of protocols LEACH, CBR and MBC based on parameters such as packet loss, average energy consumption, average control overhead, and better adaptivity to a mobile environment by using the NS-2 simulator.

A Wireless Sensor Network usually is formed by numerous wireless sensor devices. Routing is an important mechanism which will help the data to get forwarded to the right destination. Internet Protocol is an important protocol which helps in routing process. Generally the nodes in a Wireless Sensor Network are integrated and routing using IP version 4 is difficult as the address space is limited. IP version 4 uses 32 bit addressing mechanism which is not sufficient to complete the routing process. The other option is the use of Internet Protocol version 6.

Wireless sensor network (WSN) is an infrastructure less, dynamic topology, application oriented, multihoping network design with small, sensing wireless distributed nodes. [1] WSN consists of thousand of wireless node distributed in a geographical area. The distributed nodes senses the current status of its region and supply to the next upper which collects different information from different nodes and supplied final information to the

A wireless sensor network (WSN) is a collection of large number of sensor nodes and at least one base station. The sensor node is an autonomous small device that consists of mainly four units that are sensing, information gathering, processing and communication. In wireless sensor network there of many issues that are much affects in communication, processing and in deployments. The main issue is its coverage and connectivity problem. Most of the times communications does not prohibited properly amongst sensors and base station due lacking of ranges problem. Full coverage and connectivity means that every location in the field is covered by at least one node and

T. Gui in 2016 [39] studied the mechanism of SMO in the field of WSNs in the paper “A Novel Cluster-based Routing Protocol Wireless Sensor Networks using Spider Monkey Optimization.” The study additionally showed the change in traditional routing protocols in term of low-energy consumption and system quality of the network. SMO-C protocol suggested in the paper worked for Wireless sensor networks to minimize global energy consumption.

Wireless sensor networks (WSNs) are presented their abilities in many vital applications such as wildlife tracking, checking heart rates of human, military applications, traffic monitoring, etc, [1]. Wireless sensors have limited resources, including limited storage, limited processing facility, and communication capability. In addition, each sensor node is powered by a battery, which has a finite size and cannot be recharged or replaced due to environmental conditions [2-5]. Actually, Sensor nodes depend on their finite resources to survive. Due to these reasons, it is important to enhance the energy efficiency of nodes to improve the quality of the application service REF. The first problem of WSNs is to minimize energy consumption in

Wireless sensor networks are the networks that gather information such as environmental information, which there are numbers of applications of WSN such as healthcare, building monitoring, forest fire, smart home etc. WSN is capable of sensing, processing and communicating independently. However, as most of the sensor nodes are powered by non-rechargeable battery, the limitation of energy supply has considerably reduced the lifetime of the sensor network. Hence, new designs of sensor node network and energy efficient MAC (Media Access Control) and protocols for long term autonomous monitoring wireless sensor network has become the next vision.