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Top1. Introduction
Today most of the applications are running in wireless networking where anyone can access the resource from anywhere and anytime. Mobile computing, wireless sensor networks, ubiquitous computing and distributed computing are few examples of it. Now, WSNs are becoming critical to functionalities of upcoming emerging technology advancements than in the past decades, such as the Internet of Everything (IoE), smart city and digitization of world. WSNs are growing to be an important technology due to micro size sensors, increasing ability to sense, advancement in processing and communication are available in low cost. After reviewing research papers in the field of WSNs we identified issues like throughput, latency reliability and energy are very critical to it. Out of these, energy is a critical resource in the WSN because devices are independent, low powered, low computation and low storage where battery charging, and replacement is not possible. In such scenarios energy saving is of utmost importance. In the future, sensor nodes will be planned as disposable devices and unnecessary energy consumption must be avoided at every layer of communication, operating systems, application, and hardware. It is also found from the literature survey that much of the energy is consumed at data and network layers of the communication model. Hence our inspiration for this research work is energy saving in MAC sub-layer and IP layer. Today, many power management protocols exist but none of the protocols fulfill the future industry demands of the application such as scalability, load balancing and support of high traffic applications. Our major concern is to design the algorithm to optimize the energy in WSN. We are optimizing the energy to an extent that one battery will be sufficient for 5 to 6 years of continuous operation.
We can save energy at every layer of communication model, hardware, software, and operating system designing. After the literature survey found that main cause of energy consumption in communication model are data and network layer protocols. The main factors of energy consumption at data link layer are collision, overhearing, communication overhead and idle listening. Network layer protocols consume lots of energy in transmitting the packets without proper selection of route. We optimize energy at MAC layer by using sleep/wake up procedures and at network layer by designing a good clustering and routing protocol. A new energy saving algorithm for multichannel MAC (EE-MMAC) to support more bandwidth required applications has been designed. The primary objective of the proposed protocol is to reduce the energy consumption in MAC sub-layer by resolving the given multichannel issues. EE-MMAC is scalable protocol and optimizes energy by reducing the number of collisions. Proposed EE-MMAC supports IEEE 802.11 and considers its good power efficient techniques to save the energy at MAC sub-layer. When we used single channel MAC then there is a starvation problem and source station stops their packets transmission. Detection of starvation is difficult hence identification of source of starvation is very important. The main source in single channel are hidden nodes, way of carrier sensing and use of symmetric terminal. To remove this problem and to improve the data rate in high traffic applications a multichannel MAC with directional information has been proposed. Proposed EE-MMAC used two transmission modes and multichannel to provide higher data rates for high traffic applications. In this research work, our primary goal is to design a protocol that can better manage the energy resources in distributed WSNs. As a secondary goal, we aim to meet the demands of high traffic applications and guarantee load balancing and energy optimization in a WSN. In addition, NS3 simulations are used for the preliminary validation and testing.
The paper is organized in the given manner below. Section 2 shows a literature survey, MAC protocol issues and challenges, and details of relevant research works. We surveyed all aspects of MAC and Network layer regarding energy optimization. Section 3 discusses the role of multichannel in MAC layer and provides solutions for the given multichannel issues. A new “energy efficient & multichannel medium access control (EE-MMAC)” is detailed for heavy bandwidth applications. Section 4 presents the performance evaluation and simulation parameters. This section proves that improvement in the throughput, PDR, and optimization of energy in high traffic applications are brought out. Finally, Section 5, depicts the conclusions of work.