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

An ant colony optimization approach for maximizing the lifetime of heterogeneous wireless sensor networks

Maximizing the lifetime of wireless sensor networks (WSNs) is a challenging problem. Although some methods exist to address the problem in homogeneous WSNs, research on this problem in heterogeneous WSNs have progressed at a slow pace. Inspired by the promising performance of ant colony optimization (ACO) to solve combinatorial problems, this paper proposes an ACO-based approach that can maximize the lifetime of heterogeneous WSNs. The methodology is based on finding the maximum number of disjoint connected covers that satisfy both sensing coverage and network connectivity. A construction graph is designed with each vertex denoting the assignment of a device in a subset. Based on pheromone and heuristic information, the ants seek an optimal path on the construction graph to maximize the number of connected covers. The pheromone serves as a metaphor for the search experiences in building connected covers. The heuristic information is used to reflect the desirability of device assignments. A local search procedure is designed to further improve the search efficiency. The proposed approach has been applied to a variety of heterogeneous WSNs. The results show that the approach is effective and efficient in finding high-quality solutions for maximizing the lifetime of heterogeneous WSNs

Hybrid Swarm Intelligence Energy Efficient Clustered Routing Algorithm for Wireless Sensor Networks

Currently, wireless sensor networks (WSNs) are used in many applications, namely, environment monitoring, disaster management, industrial automation, and medical electronics. Sensor nodes carry many limitations like low battery life, small memory space, and limited computing capability. To create a wireless sensor network more energy efficient, swarm intelligence technique has been applied to resolve many optimization issues in WSNs. In many existing clustering techniques an artificial bee colony (ABC) algorithm is utilized to collect information from the field periodically. Nevertheless, in the event based applications, an ant colony optimization (ACO) is a good solution to enhance the network lifespan. In this paper, we combine both algorithms (i.e., ABC and ACO) and propose a new hybrid ABCACO algorithm to solve a Nondeterministic Polynomial (NP) hard and finite problem of WSNs. ABCACO algorithm is divided into three main parts: (i) selection of optimal number of subregions and further subregion parts, (ii) cluster head selection using ABC algorithm, and (iii) efficient data transmission using ACO algorithm. We use a hierarchical clustering technique for data transmission; the data is transmitted from member nodes to the subcluster heads and then from subcluster heads to the elected cluster heads based on some threshold value. Cluster heads use an ACO algorithm to discover the best route for data transmission to the base station (BS). The proposed approach is very useful in designing the framework for forest fire detection and monitoring. The simulation results show that the ABCACO algorithm enhances the stability period by 60% and also improves the goodput by 31% against LEACH and WSNCABC, respectively

A Multipath Routing Protocol Based on Clustering and Ant Colony Optimization for Wireless Sensor Networks

For monitoring burst events in a kind of reactive wireless sensor networks (WSNs), a multipath routing protocol (MRP) based on dynamic clustering and ant colony optimization (ACO) is proposed. Such an approach can maximize the network lifetime and reduce the energy consumption. An important attribute of WSNs is their limited power supply, and therefore some metrics (such as energy consumption of communication among nodes, residual energy, path length) were considered as very important criteria while designing routing in the MRP. Firstly, a cluster head (CH) is selected among nodes located in the event area according to some parameters, such as residual energy. Secondly, an improved ACO algorithm is applied in the search for multiple paths between the CH and sink node. Finally, the CH dynamically chooses a route to transmit data with a probability that depends on many path metrics, such as energy consumption. The simulation results show that MRP can prolong the network lifetime, as well as balance of energy consumption among nodes and reduce the average energy consumption effectively

Energy-Efficient Load Balancing Ant Based Routing Algorithm for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are a type of self-organizing networks with limited energy supply and communication ability. One of the most crucial issues in WSNs is to use an energy-efficient routing protocol to prolong the network lifetime. We therefore propose the novel Energy-Efficient Load Balancing Ant-based Routing Algorithm (EBAR) for WSNs. EBAR adopts a pseudo-random route discovery algorithm and an improved pheromone trail update scheme to balance the energy consumption of the sensor nodes. It uses an efficient heuristic update algorithm based on a greedy expected energy cost metric to optimize the route establishment. Finally, in order to reduce the energy consumption caused by the control overhead, EBAR utilizes an energy-based opportunistic broadcast scheme. We simulate WSNs in different application scenarios to evaluate EBAR with respect to performance metrics such as energy consumption, energy efficiency, and predicted network lifetime. The results of this comprehensive study show that EBAR provides a significant improvement in comparison to the state-of-the-art approaches EEABR, SensorAnt, and IACO

Pheromone-based In-Network Processing for wireless sensor network monitoring systems

Monitoring spatio-temporal continuous fields using wireless sensor networks (WSNs) has emerged as a novel solution. An efficient data-driven routing mechanism for sensor querying and information gathering in large-scale WSNs is a challenging problem. In particular, we consider the case of how to query the sensor network information with the minimum energy cost in scenarios where a small subset of sensor nodes has relevant readings. In order to deal with this problem, we propose a Pheromone-based In-Network Processing (PhINP) mechanism. The proposal takes advantages of both a pheromone-based iterative strategy to direct queries towards nodes with relevant information and query- and response-based in-network filtering to reduce the number of active nodes. Additionally, we apply reinforcement learning to improve the performance. The main contribution of this work is the proposal of a simple and efficient mechanism for information discovery and gathering. It can reduce the messages exchanged in the network, by allowing some error, in order to maximize the network lifetime. We demonstrate by extensive simulations that using PhINP mechanism the query dissemination cost can be reduced by approximately 60% over flooding, with an error below 1%, applying the same in-network filtering strategy.Fil: Riva, Guillermo Gaston. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Universidad Tecnológica Nacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Finochietto, Jorge Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Estudios Avanzados en Ingeniería y Tecnología. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Estudios Avanzados en Ingeniería y Tecnología; Argentin

Ant colony optimization approaches in wireless sensor network: Performance evaluation

Wireless Sensor Network (WSN) has been widely implemented in large sectors such as military, habitat, business, industrial, health and environment. WSN is part of a distributed system where elements such as routing, load balancing, energy efficiency, node localization, time synchronization, data aggregation and security need to be addressed to improve its efficiency, robustness, extendibility, applicability and reliability. Despite multiple approaches proposed to improve all these aspects, there is still room for improvement in order to enhance the capability of WSN in terms of routing and energy efficiency. Ant Colony Optimization (ACO) is one of the approaches used to extend WSN capabilities because its heuristic nature is very suitable with distributed and dynamic environments. This study covers the common WSN aspects and performance evaluation criteria in addition to the list of previous studies that have used ACO approaches in WSN

ANTMANET: a novel routing protocol for mobile ad-hoc networks based on ant colony optimisation

The core aim of this research is to present “ANTMANET” a novel routing protocol for Mobile Ad-Hoc networks. The proposed protocol aims to reduce the network overhead and delay introduced by node mobility in MANETs. There are two techniques embedded in this protocol, the “Local Zone” technique and the “North Neighbour” Table. They take an advantage of the fact that the nodes can obtain their location information by any means to reduce the network overhead during the route discovery phase and reduced the size of the routing table to guarantee faster convergence. ANTMANET is a hybrid Ant Colony Optimisation-based (ACO) routing protocol. ACO is a Swarm Intelligence (SI) routing algorithm that is well known for its high-quality performance compared to other distributed routing algorithms such as Link State and Distance Vector. ANTMANET has been benchmarked in various scenarios against the ACO routing protocol ANTHOCNET and several standard routing protocols including the Ad-Hoc On-Demand Distance Vector (AODV), Landmark Ad-Hoc Routing (LANMAR), and Dynamic MANET on Demand (DYMO). Performance metrics such as overhead, end-to-end delay, throughputs and jitter were used to evaluate ANTMANET performance. Experiments were performed using the QualNet simulator. A benchmark test was conducted to evaluate the performance of an ANTMANET network against an ANTHOCNET network, with both protocols benchmarked against AODV as an established MANET protocol. ANTMANET has demonstrated a notable performance edge when the core algorithm has been optimised using the novel adaptation method that is proposed in this thesis. Based on the simulation results, the proposed protocol has shown 5% less End-to-End delay than ANTHOCNET. In regard to network overhead, the proposed protocol has shown 20% less overhead than ANTHOCNET. In terms of comparative throughputs ANTMANET in its finest performance has delivered 25% more packets than ANTHOCNET. The overall validation results indicate that the proposed protocol was successful in reducing the network overhead and delay in high and low mobility speeds when compared with the AODV, DMO and LANMAR protocols. ANTMANET achieved at least a 45% less delay than AODV, 60% less delay than DYMO and 55% less delay than LANMAR. In terms of throughputs; ANTMANET in its best performance has delivered 35% more packets than AODV, 40% more than DYMO and 45% more than LANMAR. With respect to the network overhead results, ANTMANET has illustrated 65% less overhead than AODV, 70% less than DYMO and 60 % less than LANMAR. Regarding the Jitter, ANTMANET at its best has shown 60% less jitter than AODV, 55% jitter less than DYMO and 50% less jitter than LANMAR

Research routing and MAC based on LEACH and S-MAC for energy efficiency and QoS in wireless sensor network

The wireless sensor is a micro-embedded device with weak data processing capability and small storage space. These nodes need to complete complex jobs, including data monitoring, acquisition and conversion, and data processing. Energy efficiency should be considered as one of the important aspects of the Wireless Sensor Network (WSN) throughout architecture and protocol design. At the same time, supporting Quality of Service (QoS) in WSNs is a research field, because the time-sensitive and important information is expected for the transmitting to to the sink node immediately. The thesis is supported by the projects entitled “The information and control system for preventing forest fires”, and “The Erhai information management system”, funded by the Chinese Government. Energy consumption and QoS are two main objectives of the projects. The thesis discusses the two aspects in route and Media Access Control (MAC). For energy efficiency, the research is based on Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. LEACH is a benchmark clustering routing protocol which imposes upon cluster heads to complete a lot of aggregation and relay of messages to the base-station. However, there are limitations in LEACH. LEACH does not suit a wide area in clustering strategy and multi-hop routing. Moreover, routing protocols only focus on one factor, combining the clustering strategy and multi-hop routing mechanism were not considered in routing protocol for performance of network. QoS is supported by the MAC and routing protocol. Sensor MAC(S-MAC) makes the use of the periodically monitoring / sleeping mechanism, as well as collision and crosstalk avoidance mechanism. The mechanism reduces energy costs. Meanwhile, it supports good scalability and avoids the collision. However, the protocols do not take the differentiated services. For supporting QoS,A new route protocol needs to be designed and realized on embed platforms, which has WIFI mode and a Linux operation system to apply on the actual system. This research project was conducted as following the steps: A new protocol called RBLEACH is proposed to solve cluster on a widely scale based on LEACH. The area is divided into a few areas, where LEACH is improved to alter the selecting function in each area. RBLEACH creates routes selected by using a new algorithm to optimize the performance of the network. A new clustering method that has been developed to use several factors is PS-ACO-LEACH. The factors include the residual energy of the cluster head and Euclidean distances between cluster members and a cluster head. It can optimally solve fitness function and maintain a load balance in between the cluster head nodes, a cluster head and the base station. Based on the “Ant Colony” algorithm and transition of probability, a new routing protocol was created by “Pheromone” to find the optimal path of cluster heads to the base station. This protocol can reduce energy consumption of cluster heads and unbalanced energy consumption. Simulations prove that the improved protocol can enhance the performance of the network, including lifetime and energy conservation. Additionally, Multi Index Adaptive Routing Algorithm (MIA-QR) was designed based on network delay, packet loss rate and signal strength for QoS. The protocol is achieved by VC on an embedded Linux system. The MIA-QR is tested and verified by experiment and the protocol is to support QoS. Finally, an improved protocol (SMAC -SD) for wireless sensor networks is proposed, in order to solve the problem of S-MAC protocol that consider either service differentiation or ensure quality of service. According to service differentiation, SMAC-SD adopts an access mechanism based on different priorities including the adjustment of priority mechanisms of channel access probability, channel multi-request mechanisms and the configuring of waiting queues with different priorities and RTS backoff for different service, which makes the important service receive high channel access probability, ensuring the transmission quality of the important service. The simulation results show that the improved protocol is able to gain amount of important service and shortens the delay at the same time. Meanwhile, it improves the performance of the network effectivel

Secure and Reliable Routing Protocol for Transmission Data in Wireless Sensor Mesh Networks

Abstract Sensor nodes collect data from the physical world then exchange it until it reaches the intended destination. This information can be sensitive, such as battlefield surveillance. Therefore, providing secure and continuous data transmissions among sensor nodes in wireless network environments is crucial. Wireless sensor networks (WSN) have limited resources, limited computation capabilities, and the exchange of data through the air and deployment in accessible areas makes the energy, security, and routing major concerns in WSN. In this research we are looking at security issues for the above reasons. WSN is susceptible to malicious activities such as hacking and physical attacks. In general, security threats are classified depending on the layers. Physical, Transport, Network, Data link, and the Application layer. Sensor nodes can be placed in an unfriendly environments and it has lower power energy, computation and bandwidth, are exposed to a failure, and the WSN topology dynamically unstable. The recent wireless sensor protocols are intended for data communication transmission energy consumption. Therefore, many do not consider the security in WSN as much as they should and it might be vulnerable to attacks. Standard crypto systems methods aim to protect the authentication and integrity of data packets during the transmission stage between senders and receivers. In this dissertation we present Adel which is a novel routing protocol for exchanging data through wireless sensor mesh networks using Ant Colony Optimization (ACO) algorithm. Adel enhances security level during data transmission between sender party and receiver party in wireless network environment. Once the sensor nodes are deployed in a network, they need to inform their location and their data related to the security for the further communication in the network. For that purpose, ii an efficient mechanism is implemented in order to perform better communication among sensor nodes. Adel generates dynamic routing table using ACO algorithm with all the necessary information from network nodes after being deployed. Adel works with minimum routing restrictions and exploits the advantages of the three multicast routing styles, unicast, path, and mesh based. Since it takes a routing decision with a minimum number of nodes using the shortest path between the sender and the receiver nodes, Adel is applicable in static networks. Four essential performance metrics in mesh networks, network security analysis, network latency time, network packets drop, network delivery ratio, and network throughput are evaluated. Adel routing protocol has met the most important security requirements such as authorization, authentication, confidentiality, and integrity. It also grantees the absence of the cycle path problem in the network.This research reports the implementation and the performance of the proposed protocol using network simulator NS-2. The seven main parameters are considered for evaluation all experiments are security trust, packets drop, energy consumption, throughput, end to end delay and packet delivery ratio. The results show that the proposed system can significantly enhance the network security and connectivity level compared to other routing protocols. Yet, as expected, it did not do so well in energy consumption since our main goal was to provide higher level of security and connectivit