scholarly journals Swarm-Intelligence-Centric Routing Algorithm for Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5164
Author(s):  
Changsun Shin ◽  
Meonghun Lee

The swarm intelligence (SI)-based bio-inspired algorithm demonstrates features of heterogeneous individual agents, such as stability, scalability, and adaptability, in distributed and autonomous environments. The said algorithm will be applied to the communication network environment to overcome the limitations of wireless sensor networks (WSNs). Herein, the swarm-intelligence-centric routing algorithm (SICROA) is presented for use in WSNs that aim to leverage the advantages of the ant colony optimization (ACO) algorithm. The proposed routing protocol addresses the problems of the ad hoc on-demand distance vector (AODV) and improves routing performance via collision avoidance, link-quality prediction, and maintenance methods. The proposed method was found to improve network performance by replacing the periodic “Hello” message with an interrupt that facilitates the prediction and detection of link disconnections. Consequently, the overall network performance can be further improved by prescribing appropriate procedures for processing each control message. Therefore, it is inferred that the proposed SI-based approach provides an optimal solution to problems encountered in a complex environment, while operating in a distributed manner and adhering to simple rules of behavior.

Author(s):  
Pradeep Kumar Ts ◽  
Sayali Chitnis

The world of internet of things (IoT) and automation has been catching a robust pace to impact wide range of commercial and domestic applications for some time now. The IoT holds ad-hoc or wireless sensor networks (WSNs) at its very primary implementation level, the hardware level. The increasing requirement of these networks demands a renewed and better design of the network that improves the already existing setbacks of WSNs, which is mainly the power consumption and optimization. Routing highly affects the power consumed in the nodes in WSNs, hence having a modified routing algorithm which is specific to the application and meets its needs, particularly it is a good approach instead of having a generalized existent routing approach. Currently, for WSN having adequate number of nodes, routing involves maximum number of nodes and hops so as to reduce power consumption. However, for restricted areas and limited nodes, this scenario concludes with using up more number of nodes simultaneously resulting in reducing several batteries simultaneously. A routing algorithm is proposed in this paper for such applications that have a bounded region with limited resources. The work proposed in this paper is motivated from the routing algorithm positional attribute based next-hop determination approach (PANDA-TP) which proposes the increase in number of hops to reduce the requirement of transmission power. The aim of the proposed work is to compute the distance between the sending and receiving node and to measure the transmission power that would be required for a direct(path with minimum possible hops) and a multi-hop path. If the node is within the thresh-hold distance of the source, the packet is undoubtedly transferred directly; if the node is out of the thresh-hold distance, then the extra distance is calculated. Based on this, the power boosting factor for the source node, and if necessary, then the extra number of nodes that would be required to transmit is determined. An extra decision-making step is added to this approach which makes it convenient to utilize in varied situations. This routing approach suits the current level of robustness that the WSNs demand. 


Author(s):  
Lucia Keleadile Ketshabetswe ◽  
Adamu Murtala Zungeru ◽  
Joseph M. Chuma ◽  
Mmoloki Mangwala

Social insect communities are formed from simple, autonomous, and cooperative organisms that are interdependent for their survival. These communities are able to effectively coordinate themselves to achieve global objectives despite a lack of centralized planning, and the behaviour is referred to as swarm intelligence. This chapter presents a study of communication protocols for wireless sensor networks utilizing nature-inspired systems: social insect-based communities and natural creatures. Three types of insects are used for discussion: ants, termites, and bees. In addition, a study of the social foraging behavior of spider monkeys is presented. The performances of these swarm-intelligence-based algorithms were tested on common routing scenarios. The results were compared with other routing algorithms with varying network density and showed that swarm-intelligence-based routing techniques improved on network energy consumption with a control over best-effort service. The results were strengthened with a model of termite-hill routing algorithm for WSN.


Author(s):  
Pooja Chaturvedi ◽  
Ajai Kumar Daniel

Wireless sensor networks have gotten significant attention in recent times due to their applicability in diverse fields. Energy conservation is a major challenge in wireless sensor networks. Apart from energy conservation, monitoring quality of the environmental phenomenon is also considered a major issue. The approaches that addressed both these problems are of great significance. One such approach is node scheduling, which aims to divide the node set into a number of subsets such that each subset can monitor a given set of points known as targets. The chapter proposes a priority coding-based cluster head selection approach as an extension of the energy efficient coverage protocol (EECP). The priority of the nodes is determined on the basis of residual energy (RE), distance (D), noise factor (N), node degree (Nd), and link quality (LQ). The analytical results show that the proposed protocol improves the network performance by reducing the overhead by a factor of 70% and hence reduces the energy consumption by a factor of 70%.


2014 ◽  
Vol 672-674 ◽  
pp. 2033-2036
Author(s):  
Li Fen Li

This paper presents a new cross-layer QoS routing algorithm for wireless sensor networks. Basing on the principle of cross-layer design, the algorithm adopts delay, nodes’ load and link quality as QoS metrics. The QoS routing metrics are regarded as heuristics correction factors in ant colony algorithm (ACA). The ants are divided into a number of different populations. Through the interaction of pheromone between multi populations, the routing algorithm searches for the feasible paths in parallel and updates the pheromone in time. To overcome the slow convergence of ant colony algorithm, membership cloud model (MCL) is used to control the randomness of the ants. The simulation results demonstrate that the routing algorithm can guarantee the real time, reliability and robustness of wireless sensor networks. It can also achieve the network load balancing.


2018 ◽  
Vol 7 (2.31) ◽  
pp. 1
Author(s):  
C Cynthia, Prudhvi Krishna Saguturu ◽  
Komali Bandi ◽  
Srikanth Magulluri ◽  
T Anusha

In Wireless sensor networks and ad hoc networks nodes have a freedom to move from one place to another, they are self-configuring this type of the structure fulfil the requirements of several application. A survey on the different MANET protocols will be done in this paper. Mainly this paper will focus on the Quality of Service on the different parameters like Throughput and Delay between different protocols like AODV (Ad Hoc on Demand Distance Vector), DSDV (Destination-Sequenced Distance-Vector Routing), DSR (Dynamic Source Routing), and TORA (Temporary Ordered Routing Algorithm). DSDV is called as proactive protocol because they know everything about the nodes in the network before the communication start. DSR, AODV, TORA protocols are called reactive protocol because nodes in this network do not know anything about network. They are also called ON-DEMAND routing protocols. After this analysis you will come to know which MANET protocol is best for different application. 


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