Energy Efficient Ant Colony Algorithms for Data Aggregation in Wireless Sensor Networks

In this paper, a family of ant colony algorithms called DAACA for data aggregation has been presented which contains three phases: the initialization, packet transmission and operations on pheromones. After initialization, each node estimates the remaining energy and the amount of pheromones to compute the probabilities used for dynamically selecting the next hop. After certain rounds of transmissions, the pheromones adjustment is performed periodically, which combines the advantages of both global and local pheromones adjustment for evaporating or depositing pheromones. Four different pheromones adjustment strategies are designed to achieve the global optimal network lifetime, namely Basic-DAACA, ES-DAACA, MM-DAACA and ACS-DAACA. Compared with some other data aggregation algorithms, DAACA shows higher superiority on average degree of nodes, energy efficiency, prolonging the network lifetime, computation complexity and success ratio of one hop transmission. At last we analyze the characteristic of DAACA in the aspects of robustness, fault tolerance and scalability.Comment: To appear in Journal of Computer and System Science

Performance Evaluation of Reactive Routing Protocols in MANETs in Association with TCP Newreno

We inspect the performance of TCP NewReno protocol for data transfer in Mobile Ad hoc networks (MANETs). Dynamic Source Routing (DSR) protocols and AdHoc On-demand Distance Vector (AODV) are standard reactive routing protocols widely used in MANETs. In addition we also have to consider Transmission Control Protocol (TCP) as essential for MANETs since it is one of the widely used internet protocol for dependable data transmission. TCP has its variants namely TCP Reno, TCP NewReno , TCP Vegas and TCP SACK. In this paper we are evaluating the performance of DSR and AODV in association with TCP Newreno with respect to various parameters such as Average throughput, instant throughput, residual energy, packet delivery ratio. The ns-2 network simulator was used for simulation

Multipath Ant Colony Optimization Algorithm (MBEEACO) to Improve the Life Time of MANET

MANET selects a path with least number of intermediate nodes to reach the destination node. As the distance between each node increases, the quantity of transmission control increases. The power level of nodes affects the simplicity with which a route is constituted between a couple of nodes. This research paper utilizes the swarm intelligence technique through the artificial bee colony (ABC) algorithm to optimize the energy consumption in a dynamic source routing (DSR) protocol in MANET. The ABC algorithm is used to identify the optimal path from the source to the destination to overcome energy problems. The performance of the proposed MBEEACO algorithm is compared with DSR and bee-inspired protocols. The comparison was conducted based on average energy consumption, average throughput, average end-to-end delay, routing overhead, and packet delivery ratio performance metrics, varying the node speed and packet size. The proposed MBEEACO algorithm is superior in performance than other protocols in terms of energy conservation and delay degradation relating to node speed and packet size

A Survey on Underwater Acoustic Sensor Network Routing Protocols

Underwater acoustic sensor networks (UASNs) have become more and more important in ocean exploration applications, such as ocean monitoring, pollution detection, ocean resource management, underwater device maintenance, etc. In underwater acoustic sensor networks, since the routing protocol guarantees reliable and effective data transmission from the source node to the destination node, routing protocol design is an attractive topic for researchers. There are many routing algorithms have been proposed in recent years. To present the current state of development of UASN routing protocols, we review herein the UASN routing protocol designs reported in recent years. In this paper, all the routing protocols have been classified into different groups according to their characteristics and routing algorithms, such as the non-cross-layer design routing protocol, the traditional cross-layer design routing protocol, and the intelligent algorithm based routing protocol. This is also the first paper that introduces intelligent algorithm-based UASN routing protocols. In addition, in this paper, we investigate the development trends of UASN routing protocols, which can provide researchers with clear and direct insights for further research

FTDA: Performance Enhancement of WSN using Fuzzy based Traffic Data Analysis

In the present time in Wireless Sensor Network plays an essential role in the monitoring of different physical phenomena. Monitoring of city traffic data analysis is very important in different metro cities due to rapid increase in population.  This research work proposes a model for traffic data analysis using wireless sensor network  incorporated with fuzzy technique. The proposed model is tested for performance parameters such as node dead rate , data packed received. The proposed model improved the efficiency compared to existing techniques of the WSN network for traffic data collection and analysis

A Review of Various Swarm Intelligence Based Routing Protocols for Iot

The paper provides insight into various swarm intelligence based routing protocols for Internet of Things (IoT), which are currently available for the Mobile Ad-hoc networks (MANETs) and wireless sensor networks (WSNs). There are several issues which are limiting the growth of Internet of Things. These include the reliability, link failures, routing, heterogeneity etc. The MANETs and WSNs routing issues impose almost same requirements for IoT routing mechanism. The recent work of the worldwide researchers is focused on this area. protocols are based on the principles of swarm intelligence. The swarm intelligence is applied to achieve the optimality and the efficiency in solving the complex, multi-hop and dynamic requirements of the wireless networks. The application of the ACO technique tries to provide answers to many routing issues. Using the swarm intelligence and ant colony optimization principles, it has been seen that, the protocols’ efficiency definitely increases and also provides more scope for the development of more robust, reliable and efficient routing protocols for the IoT. As the various standard protocols available for MANETs and WSNs are not reliable enough, the paper finds the need of some efficient routing algorithms for IoT