Govind P. Gupta

Energy and trust aware mobile agent migration protocol for data aggregation in wireless sensor networks

Abstract Recently, the use of mobile agents in wireless sensor networks (WSNs) has emerged as the topic of extensive research due to their efficient utilization of network bandwidth and energy, and flexibility of their use for different WSN applications. Most of the proposed mobile agent based schemes use static itineraries for agents׳ migration that are computed at the sink using a centralized algorithm. These centralized algorithms require global knowledge of sensor distribution, which is difficult to obtain accurately. Other issue with static itinerary based agent migration is that an agent may not move along its itinerary due to node failures or malicious node attacks. In order to solve these issues, we first propose a framework for trust evaluation to identify the malicious behavior of sensor nodes and then give a localized distributed protocol, called energy and trust aware mobile agent migration (ETMAM) protocol for periodic data gathering application. The results of our simulation study show that the ETMAM protocol is effective in improving resilience against node failures or malicious nodes attacks.

An Energy Efficient Distributed Approach-Based Agent Migration Scheme for Data Aggregation in Wireless Sensor Networks

Abstract The use of mobile agents for collaborative processing in wireless sensor network has gained considerable attention. This is when mobile agents ar e used for data aggregation to exploit redundant and correlated data. The efficiency of agent-based data aggregation depends on the agent migration scheme. However, in general, most of the proposed schemes are centralized approach-based schemes where the sink node determines the migration paths for the agents before dispatching them in the sensor network. The main limitations with such schemes are that they need global network topology information for deriving the migration paths of the agents, which incurs additional communication overhead, since each node has a very limited communication range. In addition, a centralized approach does not provide fault tolerant and adaptive migration paths. In order to solve such problems, we have proposed a distributed approach-based scheme for determining the migration path of the agents where at each hop, the local information is used to decide the migration of the agents. In addition, we also propose a local repair mechanism for dealing with the faulty nodes. The simulation results show that the proposed scheme performs better than existing schemes in the presence of faulty nodes within the networks, and manages to report the aggregated data to the sink faster.

Multiple Mobile Agents based Data Dissemination Protocol for Wireless Sensor Networks

Energy Efficient and reliable data dissemination in wireless sensor network is an important research issue since the network consists of low cost nodes with limited resources. Mobile agent-based data dissemination (MADD) approach that deploys multiple mobile agents for the data gathering task is a flexible, robust, and distributed solution to the data dissemination problem in wireless sensor networks. However the manners in which mobile agents follow the itineraries (order of visited sensor nodes) have an impact on the efficiency of the data gathering. In this paper, we propose a multiple mobile agents with dynamic itineraries based data dissemination (MMADIDD) protocol that not only adapts to unexpected node failures but also prolongs the network lifetime.

Integrated clustering and routing protocol for wireless sensor networks using Cuckoo and Harmony Search based metaheuristic techniques

Abstract Uniform energy consumption and its optimization is a major concern for designing the clustering and routing protocol for large scale wireless sensor networks. Most of the existing nature-inspired computing based solutions for cluster-based routing problem for wireless senor network, suffer from unbalanced energy consumption issues. This is due to fact that nodes near to the sink are overloaded in terms of traffic load. In this research work, problem of energy balanced node clustering and routing between cluster heads and the sink are considered. This paper proposed an improved cuckoo search-based energy balanced node clustering protocol which uses a novel objective function for uniform distribution of cluster heads. In addition, an improved harmony search based routing protocol is proposed for routing of the data packet between cluster heads and the sink. The performance of the proposed integrated clustering and routing protocol is evaluated using the average energy consumption, the number of alive nodes, number of dead nodes and network lifetime. The proposed Cuckoo–Harmony Search-based integrated clustering and routing protocol shows significant improvement over the state-of-art protocols.

Energy efficient data gathering using prediction-based filtering in wireless sensor networks

In wireless sensor network, sensor readings generated by nearby nodes are redundant and highly correlated, both in space and time domains. Since transmitting redundant and highly correlated data incurs a huge waste of energy and bandwidth, spatial and temporal correlation should be exploited in order to reduce redundant data transmission. In this paper, we propose an energy efficient data gathering protocol that uses a prediction-based filtering EEDGPF mechanism to solve the problem of redundant data transmissions. Our data gathering protocol organises a WSN into clusters, using data similarity that exists in readings of sensor nodes and cluster heads and uses a GARCH 1, 1 model-based non-linear predictor to exploit the temporal correlation of sensor readings. Experimental results over real dataset show that our protocol significantly outperforms linear predictor AR3-based protocol proposed in Jiang et al. 2011, in terms of number of data packets delivered, number of successful predictions and average energy consumption.

Performance evaluation of similarity-based link prediction schemes for social network

Social network is a platform where people can share their information, make new connections, and explore the information about the different events occurring in society. In recent year, prediction for new link in the social network has been attracted many researchers. Link Prediction in social network refers to finding new connections that will occur between people in the future. It finds the absence and presence of edge in a social network. In this paper, we have explored well known similarity based link prediction algorithms and discuss their performance in terms of accuracy, precision, and recall. The experimental results show that common neighbours and Jaccard coefficient based algorithms perform better than other algorithms in term of accuracy.

Performance evaluation of agent and non-agent based data dissemination protocols for wireless sensor networks

One of the fundamental requirements of energy-constrained wireless sensor networks is to prolong the network lifetime which strongly depends on the data dissemination protocol used. A variety of different energy efficient data dissemination protocols are proposed in recent years. However there is little performance evaluation information on each protocol and no realistic performance comparison in the same scenario between them is available. In this paper, we present the first comprehensive performance evaluation and comparison of agent-based and non-agent based data dissemination protocols. Our simulation study provides useful insights for the network designer such as which data dissemination protocols scale well, reduce overall energy consumption or improve task completion time.

Efficient coverage and connectivity aware data gathering protocol for wireless sensor networks

In wireless sensor networks, a fundamental research issues in designing a protocol is how to minimize energy consumption and prolong the network lifetime, while ensuring the required spatial coverage as well as connectivity. In this paper, we present an efficient coverage and connectivity aware data gathering (ECCDG) protocol for periodic data gathering applications which ensure sufficient coverage and connectivity in the network. ECCDG reduces and balance the energy consumption by periodically selecting a set of connected active node for forwarding the sensed data from the rest of the sensor nodes. The selected set of connected active node work as a relay nodes. Each normal node transmits its observed sensory data to its closest active nodes and an active node forwards the sensed data via active relay nodes toward the sink. The performance of the proposed protocol is evaluated and compared with most recent protocols. Simulation results show that ECCDG consumes less energy consumption and has a better connectivity of the network compare to the state-of-art protocols.

Towards scalable and load-balanced mobile agents-based data aggregation for wireless sensor networks

Abstract In recent years, mobile agents have been employed for collaborative processing in wireless sensor networks (WSNs), where agents migrate from node to node, progressively aggregate data and return to the sink with the results. However, when an agent migrates through its itinerary, its size linearly grows and it may become bloated in size. We show through mathematical analysis that the existence of the bloated state problem in mobile agents-based data aggregation causes increase in nodes energy consumption as well as response time. To solve the bloated state problem, we propose a scalable and load-balanced scheme for mobile agents-based data aggregation. The proposed protocol is evaluated through simulation experiments under different network scenario and compared with some well-known existing schemes. The proposed scheme shows improved performance in terms of energy consumption, response time and network lifetime.

A novel DV-Hop algorithm based on Gauss-Newton method

In numerous uses of wireless sensor networks (WSN), sensor nodes are required to transmit its sensed data along with the location information. Due to this reason, determining the location of the deployed sensor nodes is a fundamental research issue in WSN. In literature, there are many types of localization methods are proposed to solve this problem. Among them, DV-Hop is most widely known and discussed localization algorithm due to its simplicity and low cost. However, the main problem with the DV-Hop algorithm is its high positioning error. This problem arises due to the use of linear method such as least square method for solving the non-linear equations during the estimation of the position of sensors, which affects the localization precision. To overcome this problem, this paper introduces an enhanced DV-Hop algorithm that uses a non-linear method called Gauss-Newton method to achieve more accurate estimated location than the traditional DV-Hop algorithm. Keeping in mind the end goal to demonstrate the adequacy of the proposed enhanced DV-Hop calculation, its execution is surveyed and stood out from traditional DV-Hop through extensive simulations.