Energy efficient multipath ant colony based routing algorithm for mobile ad hoc networks

This work proposes an approach for improving energy-efficiency and thus increasing network lifetime in wireless sensor network (WSN) using a logical energy tree (LET). In our scheme, LET is constructed using the remaining available energy in each node. Two routing algorithms are framed based on LET: one with centralized sink node called LETCSN and the other with centralized sink node and secondary sink nodes called LETSSN. sensor nodes are deployed in some fixed patterns. A mathematical model is devised to understand the effect of node deployment pattern on improving network lifetime. Both proposed routing algorithms are evaluated with seven different deployment patterns, simulated in ns-2 and are compared with the existing classic algorithms based on the number of data packets, throughput, network lifetime, and data packet's average network lifetime product. Our evaluation and simulation results show that LETSSN maximizes the network lifetime for all node-deployment patterns taken into consideration.

Wide usage of wireless sensor network (WSN) is the reason for development of many routing protocols. Recent advances in WSN observe the increased interest in the potential use in applications like Military, Environmental, Health, Vehicular, Mechanical stress levels on attached objects, disaster management etc. Wireless sensor networks are callously restricted by storage capacity, energy and computing power. So it is essential to design an energy efficient aware protocol in order to augment the network lifetime. WSN also has the influencing features to perform remote communication, it is also shrouded with various loopholes in its precise operation, where majority of the communication issues are raised from deployment of existing standards of routing protocols and algorithm. Sensors are expected to be remotely deployed in unnoticed environments. Routing as one key technologies of wireless sensor network has now become very important research work because the applications of WSN is everywhere, it is impractical that there is a routing protocol suitable for all applications. In this paper, a review on routing protocol in WSNs is carried out which are classified as data-centric, hierarchical and location based depending on the network structure. Then some of the multipath routing protocols which are widely used in WSNs like Multipath Multispeed Protocol (MMSPEED), Braided Multipath Routing Protocol, Energy-Aware Routing to improve network performance are also discussed. Massive research work has already been carried out in past to introduce some of the effective routing protocols to enable robust communication system in WSN. Advantages and disadvantages of each routing algorithm are discussed thereafter. This paper also discusses the critical open issues that are yet to be solved. This paper compares and summarizes the performances of routing protocols.

Wireless sensor networks congestion occurs easily due to its centralized traffic pattern. Normally, mono-sync wireless sensor network experiences multiple traffic flow congestion in the dense environment of the network, which leads to excess energy consumption and severe packet loss. To overcome these issues, a congestion detection and alleviation mechanism using cluster based heuristic optimized hierarchical routing protocol is proposed in this paper. Here, congestion detection and alleviation utilize the features of sensor nodes. The congestion is categorized into two types: (i) node level congestion and (ii) link level congestion. The node level congestion is detected by assessing the buffer utilization and the interval amid the consecutive data packets. The link level congestion is considered with computing link usage utilizing back-off step of round robin carrier sense multi-access with collision avoidance. Congestion detection and alleviation reactively affected node/link through cuckoo hosted rider search multi-hop routing algorithm. It has two phases: the cluster head selection and multi-path routing. Cluster head selection is performed through Taylor multiple random forest kernel fuzzy C-means clustering algorithm and multi-path routing is performed through cuckoo hosted rider search multi-hop routing algorithm. The simulation of the proposed method is done in network simulator tool. Here, the performance metrics, like packet delivery ratio, delay, energy consumption, packet drop, overhead, network lifetime and throughput are calculated. The experimental outcomes of the proposed technique shows 11.6%, 18.4% and 28.1% lower delay, 78.2%, 65.4% and 52.6% higher packet delivery ratio, and 29.2%, 37.4% and 40.8% lower packet drop compared with the existing methods, like congestion detection and alleviation using multi-attribute decision-making in optimization-based hybrid congestion alleviation routing protocol in wireless sensor networks, congestion detection and alleviation using hybrid K-means with greedy best first search algorithms in packet rate reduction utilizing adaptive weight firefly algorithm ant colony optimization based routing protocol in wireless sensor networks and congestion detection and alleviation using multi-input time on task optimization algorithm for altered gravitational search algorithm routing protocol in wireless sensor networks.

In this paper we propose a novel routing algorithm called Bees_Ants algorithm. This algorithm is a combination of ant colony based routing algorithm (ARA) and BeeHive based routing algorithm. The proposed routing algorithm depends on splitting the network into two parts; one is a fixed network and the other is a mobile ad hoc network (MANET), then applying the ant colony based routing algorithm on the mobile part and the BeeHive based routing algorithm on the fixed one. After comparing the proposed algorithm with the ARA algorithm, it shows promising results in terms of propagation delay, queue delay, and number of hops.

Recent developments in wireless sensor networks (WSNs) have led to significant advances in energy-efficient routing protocols through the integration of deep learning and bio-inspired optimization algorithms. WSNs face critical challenges due to limited battery capacity, computational constraints, and dynamic network topology. This review article provides a comprehensive comparative analysis of state-of-the-art approaches for energy optimization in WSNs, focusing on clustering and routing protocols. We examine three major publications that propose hybrid frameworks combining deep learning architectures (CapsNet, ResNet-50) with metaheuristic optimization algorithms (ETSA, SOPSO, ACO). The analysis categorizes these protocols based on network architecture, energy models, optimization strategies, and performance metrics. We compare their effectiveness in extending network lifetime, reducing energy consumption, improving packet delivery ratio, and minimizing transmission delay. The comparative study demonstrates that hybrid deep learning-swarm intelligence approaches achieve 18-38% improvement in network lifetime, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{1 2} \boldsymbol{-} \mathbf{1 4 \%}$</tex> reduction in energy consumption, and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{1 5} \boldsymbol{-} \mathbf{2 4 \%}$</tex> lower delay compared to traditional protocols. This article serves as a comprehensive reference for researchers and practitioners working on nextgeneration energy-efficient WSN deployments.

ABSTRACTWireless sensor networks, or WSNs, are essential for energy monitoring, home automation, the medical industry, computing, and other fields. The two problems with wireless sensor network are the network lifetime and data transmission delay. The cluster head selection (CHS) is a difficult task. Therefore, a novel Hybrid Archimedes and Arithmetic Optimization Algorithm for Cluster Head Selection and Multipath Routing in Wireless Sensor Network (HYB‐AO‐AOA‐CHS‐WSN) is proposed in this paper. The proposed HYB‐AO‐AOA integrates Archimedes and Arithmetic optimization algorithm (AO‐AOA). The stimulation of sensor nodes initiates the CHS process. The stimulated sensor nodes are evaluated separately for delay, energy, node degree, intercluster distance, and intracluster distance for determining the cluster heads. Then, the multipath routing is handled by the HYB‐AO‐AOA technique. The proposed HYB‐AO‐AOA‐CHS‐WSN model is implemented in MATLAB. The metrics, like delay, number of alive nodes, throughput, and residual energy is examined. The proposed SRD‐DCGAN approach attains 25.72%, 21.32% and 19% higher throughput, 26.56%, 21.35% and 32.09% lower delay than the existing techniques.

Energy utilization in a wireless sensor network (WSN) is a major concern. In WSN we cannot use rechargeable batteries, because sensor nodes are mostly deployed in areas which are not easily accessible. In this paper, we consider a one dimensional (1-D) network and look at reducing energy during routing of packets. To increase the network lifetime of a WSN, routing protocol should not unnecessarily use all the nodes in the network, instead use minimum number of nodes. So relay node selection plays an important role in energy reduction. In this paper, we use two major algorithms: energy saving via opportunistic routing algorithm (ENS_OR) and geographic random forwarding algorithm (GeRaF) for reducing energy consumption and along with these, we implement sleep mode. We show that use of sleep mode improves network lifetime by reducing energy consumption.

Congestion-aware ant colony based routing algorithms for efficient application execution on Network-on-Chip platform

Wireless sensor network is a new generation of networks in which the main aim is to collect data from the surrounding environment of network sensors. The major differences of wireless sensor networks with other networks are limited energy resources and relatively low processing capabilities. Therefore, managing power and reducing energy consumption are of great importance in these networks. In this paper, there was presented a mechanism for Wireless sensor network routing which can be more effective regarding the criteria of route length, end–to–end delay and network node energy for the quality of mechanism service. The proposed method used ant colony–based routing algorithm and local enquiry to find optimal routes. Also, a fuzzy inference system was used to determine the route quality which showed better performance compared with equation of route quality. The results of simulating mechanism showed that energy consumption and network efficiency had improved compared with those of previous methods. DOI: http://dx.doi.org/10.11591/ijece.v3i5.3628

Mobile ad hoc network (MANET) is a collection of wireless mobile nodes. It dynamically forms a temporary network without using any pre existing network infrastructure or centralized administration i.e. with minimal prior planning. All nodes have routing capabilities and forward data packets to other nodes in multi-hop fashion. As the network is dynamic, the network topology continuously experiences alterations during deployment. The biggest challenge in MANETs is to find a path between communicating nodes. The considerations of the MANET environment and the nature of the mobile nodes create further complications which results in the need to develop special routing algorithms to meet these challenges. Swarm intelligence, a bio-inspired technique, which has proven to be very adaptable in other problem domains, has been applied to the MANET routing problem as it forms a good fit to the problem. In ant societies the activities of the individuals are not regulated by any explicit form of centralized control but are the result of self-organizing dynamics driven by local interactions and communications among a number of relatively simple individuals. This unique characteristic has made ant societies an attractive and inspiring model for building new algorithms and new multi-agent systems. In this paper, we have studied and reviewed Ant Colony based routing algorithms and its variants. Finally, a performance evaluation of the original ARA and the EARA is carried out with respect to each other.

This paper introduces a new IEEE standard, IEEE 802.15.5,which provides mesh capability for wireless personal area network (WPAN) devices. The standard provides an architectural framework enabling WPAN devices to promote interoperable, stable, and scalable wireless mesh topologies. It is composed of two parts: low-rate WPAN mesh and high-rate WPAN mesh. In this paper, we present only low-rate WPAN mesh because it is designed to support wireless sensor networks. IEEE 802.15.5 low-rate part is a light-weight scalable mesh routing protocol that caters well to the requirements of resource-constrained wireless sensor networks. By binding logical addresses to the network topology, IEEE 802.15.5 obviates the need for route discovery. This eliminates the initial route discovery latency, saves storage space and reduces the communication overhead and energy consumption. A distributed link state scheme is further built atop the block addressing scheme to improve the quality of routes, robustness, and load balancing. The routing scheme scales well with regard to various performance metrics. The standard also provides enhanced functions such as multicast, reliable broadcast, power saving, time synchronization, route tracing and portability. We also present the performance evaluation of major functions performed with a 50-nodes tested deployed over a whole floor (100 × 140 ft2) at CUNY Engineering building. The results testify that the IEEE 802.15.5 will serve well for wireless personal area networks and wireless sensor networks.

Wireless sensor networks (WSN) play a key role in enabling wireless communication technology among several nodes to remotely communicate and exchange information. WSN consists of tiny sensor nodes equipped with battery, scattered in an area to gather information around an environment and send to data collection node known as sink or base station (BS). WSN have been widely used in various applications like agriculture, fire detection, health care and military and has become imperative necessity for future revolutionary area like UAV (unmanned aerial vehicles), IoT (Internet of things) and smart cities which employs large scale sensor nodes. However sensor nodes are limited to battery, memory, low computational power, resource and bandwidth. Continues sensing of events, makes node to drain its battery faster and goes dead fast. For resource constrained WSN, hierarchical cluster based approaches are considered as energy efficient and improves network performance for large scale WSN. Minimizing energy consumption and extending network lifetime are major challenging issues of WSN, clustering methods with optimized routing have offered solution to optimize energy utilization. To balance energy consumption and improve network lifetime many existing hierarchical clustering approaches have been proposed, however existing method does not consider rotation of cluster head (CH) and considers cluster head selection based on residual energy and distance parameter. In this paper we propose an improved energy efficient cluster tree (IEECT) based routing to improve energy efficiency of hierarchical cluster. IEECT considers modification of existing LEACH (Low energy adaptive clustering hierarchy) protocol to improved energy efficient LEACH by considering energy parameters like residual node energy and average network energy. IEECT accounts optimal number of cluster head (CH) and selection of CH is done using threshold value among sensor nodes. Proposed IEECT combines tree based routing and data aggregation scheme to maintain desirable quality of service. Simulation experiments are carried out by using network simulator. Performance of IEECT is evaluated in terms of PDR, delay, energy consumption, network lifetime and overhead.

In Mobile Ad-hoc networks (MANET), power conservation and utilization is an acute problem and has received significant attention from academics and industry in recent years. Nodes in MANET function on battery power, which is a rare and limited energy resource. Hence, its conservation and utilization should be done judiciously for the effective functioning of the network. In this paper, a novel protocol namely Energy Reduction Multipath Routing Protocol for MANET using Recoil Technique (AOMDV-ER) is proposed, which conserves the energy along with optimal network lifetime, routing overhead, packet delivery ratio and throughput. It performs better than any other AODV based algorithms, as in AOMDV-ER the nodes transmit packets to their destination smartly by using a varying recoil off time technique based on their geographical location. This concept reduces the number of transmissions, which results in the improvement of network lifetime. In addition, the local level route maintenance reduces the additional routing overhead. Lastly, the prediction based link lifetime of each node is estimated which helps in reducing the packet loss in the network. This protocol has three subparts: an optimal route discovery algorithm amalgamation with the residual energy and distance mechanism; a coordinated recoiled nodes algorithm which eliminates the number of transmissions in order to reduces the data redundancy, traffic redundant, routing overhead, end to end delay and enhance the network lifetime; and a last link reckoning and route maintenance algorithm to improve the packet delivery ratio and link stability in the network. The experimental results show that the AOMDV-ER protocol save at least 16% energy consumption, 12% reduction in routing overhead, significant achievement in network lifetime and packet delivery ratio than Ad hoc on demand multipath distance vector routing protocol (AOMDV), Ad hoc on demand multipath distance vector routing protocol life maximization (AOMR-LM) and Source routing-based multicast protocol (SRMP) algorithms. Hence, the AOMDV-ER algorithm performs better than these recently developed algorithms.

In this paper we investigate the benefits of a heterogeneous architecture for wireless sensor networks composed of a few resource rich mobile nodes and a large number of simple static nodes. These mobile nodes can either act as mobile relays or mobile sinks. To investigate the performance of these two options and the trade-offs associated with these two options, we first consider a finite network. We then compute the lifetime for different routing algorithms for three cases (i) when the network is all static (ii) when there is one mobile sink and (iii) when there is one mobile relay. We find that using the mobile node as a sink results in the maximum improvement in lifetime. We contend however that in hostile terrains, it might not always be possible for the sink to be mobile. We then investigate the performance of a large dense network with one mobile relay and show that the improvement in network lifetime over an all static network is upper bounded by a factor of four. Also, the proof implies that the mobile relay needs to stay only within a two hop radius of the sink. We then construct a joint mobility and routing algorithm which comes close to the upper bound. However this algorithm requires all the nodes in the network to be aware of the location of the mobile node. We then proposed an alternative algorithm, which achieves the same performance, but requires only a limited number of nodes in the network to be aware of the location of the mobile. We finally compare the performance of the mobile relay and mobile sink and show that for a densely deployed sensor field of radius R hops, we require O(R) mobile relays to achieve the same performance as the mobile sink.

Major Wireless Sensor Network designs are focused on improving the network lifetime. The data aggregation process is the simplest way to achieve this. The PEGASIS routing protocol is a promising approach for efficient data aggregation in Wireless Sensor Networks. It is also reported in the literature that the PEGASIS performs better than LEACH and HEED protocol towards improving the network lifetime. However, in PEGASIS, the selection of a leader located far away from the base station still remains exposed to higher energy consumption for sending aggregated data. In this paper, we propose an enhancement to the chain formation process of PEGASIS to further improve its lifetime, and called it PEGASIS with Improved Network Lifetime (PEGASIS-INL). In contrast to original PEGASIS protocol, the PEGASIS-INL selects a node as a leader only if it is within a strong communication range of base station. A multiple overlapped chain formation and the aggregation technique is used for transmission of sensed information to the base station. Experimental results demonstrate that the PEGASIS-INL algorithm outperforms PEGASIS in terms of the product of consumed energy and delay, weighting the overall performance of both the energy consumption and the network lifetime.