An Intelligent Opportunistic Routing Protocol for Big Data in WSNs

An Intelligent Opportunistic Routing Protocol for Big Data in WSNs

Deep Kumar Bangotra (Department of Higher Education, J&K Govt. Srinagar, India), Yashwant Singh (Central University of Jammu, J&K, Srinagar, India) and Arvind Kumar Selwal (Central University of Jammu, J&K, Srinagar, India)
DOI: 10.4018/IJMDEM.2020010102
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Opportunistic routing (OR) is an emerging and promising data communication protocol in wireless sensor networks (WSNs). The OR becomes more important when the routing of data is Big Data (BD) generated from multidimensional distributed sensors nodes. The central idea behind OR is overhearing and coordination between relay nodes in the forwarders list and management of multidimensional BD. It uses the salient broadcast feature of the wireless medium for achieving advanced reliability and maximizing the communication range. This article presents the basic concepts of WSN, reviews different OR protocols, and describes the use of different machine learning (ML) techniques in routing BD. Current issues and challenges associated with WSN in general and OR in particular are also presented in this article.
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The WSN are the networks where the necessity of low information rate and low power advancements for a sensor node play a very pivotal role. The WSN are initially spurred by the battlefield surveillance but with the steady progression of technologies in the domain of WSN, their extension and utilization have been cutting-edge in the field of Monitoring of Industrial Processes, Structural Health Monitoring, etc. (Alsheikh, Lin, Niyato, & Tan, 2014). A WSN characteristically comprised of four basic constituents i.e. i) an arrangement of distributed or localized sensors (nodes), ii) a communicating network, iii) a principal point of information gathering and iv) a set of computing resources at the central point (Sohraby, Minoli, & Znati, 2007). Being application focussed is one of the highlights of WSN. Figure 1 represents different components of a sensor node along with unique characteristics of each component. WSN nodes send data from one node to another so that the observed data reaches its destination. The sensor nodes deployed over large area generates the multidimensional huge data continuously that ultimately takes the shape of Big Data. The process of finding suitable path for sending big data from source node to destination node is called routing. Routing of big data in constrained WSN is very challenging due to the inherent characteristics that distinguish these networks from traditional networks like mobile Adhoc networks or cellular networks. All the operations performed by the sensor nodes in the network i.e. acquisition of multidimensional data, communication (routing) and processing have its toll on the energy. The maximum battery power is exhausted during the transmission or communication operation of big data. In WSN, it is the routing operation which demands maximum consumption of resources (Ben, Rajoua, & Ridha, 2018).

Figure 1.

Sensor node and its components (Devi, Shivaraj, & Manjula, 2014)


The problem of energy consumption in routing big data from source to destination is managed with the use of a special type of routing protocol known as the Opportunistic Routing Protocol. The Opportunistic Routing (OR) is also known as anypath routing. It has gained huge importance in the recent years of research in WSN (Hsu, Liu, & Seah, 2011). In OR, best opportunities will be searched to communicate the data packets from source to target (Shruti Pandey, 2017) by taking broadcast feature of the wireless medium into account. The OR protocols proposed recently are still struggling with issues pertaining to energy efficiency and reliable delivery of data packets.

The development of models and algorithms is possible with one of the applications of Artifical Intelligence so that systems learn different rules (Jesus, Casimiro, & Oliveira, 2017). In the recent past, machine learning techniques have seen significant application in resolving network-based challenges (i.e. routing, security, etc.) and application-oriented problems (QoS).

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