Energy Hole Minimization in Wireless Mobile Ad Hoc Networks Using Enhanced Expectation-Maximization

Mobile Ad hoc Network (MANET) basically, is a collection of mobile hosts incorporating wireless interfaces that forms a transitory autonomous network. They do not base on fixed infrastructure or central administration, rather work on the principle of self-organized interconnections among mobile nodes. Fundamentally, in MANET when nodes come inside the transmission range of neighboring nodes', they can be detected by each other and can communicate directly. However for communication outside this range they have to depend on some other nodes to relay the messages .This is where routing protocols have to play a very important role. Literature for improving the performance of routing protocol is available in abundance. Among these comes, the hierarchical/cluster-based routing protocols that claim to reduce control overheads. Clustering in Mobile Ad hoc Networks (MANETs) has proved to be advantageous compared to the traditional networks. However the highly dynamic and unstable nature of MANETs makes it intricate for the cluster based routing protocols to split a mobile network into clusters and determination of cluster heads for each cluster. Although much previous research has concentrated on cluster-head selection in MANETs, not much effort has been done on the security side of cluster-head selection. This paper emphasize that secure cluster head selection in MANETs has an intense effect on network performance. Specifically, we stress that in ad hoc network where all the participants are self controlled, security is an essential aspect and the effective cluster-head selection can improve network throughput. We propose a secure and effective cluster-head Selection scheme using a cross-layer approach that integrates cluster-head discovery and selection functionality with network ad hoc routing mechanisms and the lower layer drivers built-in the system. Besides, proposed scheme handle the disconnections in ad hoc network due to the effects of topology changes and battery depletion. This scheme allows clients to switch to better cluster-head nodes as network topology changes. Hence, provides better performance to network.

The Routing Approaches in Mobile Ad-hoc Network have almost entered the saturated arena. But still there are available options of perfection in this meadow. The task of improving the clustering technique is one of the fields which is under rated as a research topic for further improvement of routing. Clustering based MANET routing protocols, which are popular in terms of efficiency, simplicity and usability mostly use circular based clustering techniques. And the election of cluster head is done through the use conventional approaches. This particular paper is mainly focused to launch a new-fangled clustering technique through which it is possible to improve the routing performance of existing protocols. Another important aspect of this paper is to provide a cluster head selection algorithm which can effectively maintain the clusters and provides more stability. Proposed clustering idea is useful for geographically related nodes effectively in different turf of routing. To maintain the clusters and their stability, it provides a new idea to select cluster head within the cluster, also the election of secondary cluster head for avoiding further election immediately after the unavailability of primary cluster head. This idea is evaluated in network simulator and it outperforms the existing clustering techniques.

Energy minimization in sensor nodes is the problem in wireless sensor networks (WSNs). The most widely accepted method to preserve energy of sensor nodes is clustering. In cluster based networks, energy consumption is higher in the nodes which are closer to the sink as compared to the nodes which are located farther away from base station (BS). Various unequal clustering algorithms were proposed in the past to correct this issue. The major drawbacks in the findings are that the nodes, which join a specific cluster head, cause overburdening of the cluster head. In this paper, we present an algorithm namely energy efficient unequal sector clustering (EUSC) using multi-sector and unequal clustering approaches which improve the network’s energy efficiency. EUSC divides the network into multiple sectors based on nodes distances from BS. Selection of cluster heads in each sector is based on nodes distances to BS, residual energy and neighbor nodes proximities in that sector. Selection of a relay cluster head for data transmission is also based on residual energy, nodes distances to BS and queue length of nodes. In this paper, we have carried out some theoretical analysis of the nodes energy consumption in each sector and derived an expression for optimal number of clusters in each sector to minimize nodes energy consumption. Various simulations were carried out with MATLAB package to differentiate the competency of the proposed EUSC algorithm with that of the existing protocols ECHA and ‘PSO based protocol’. Simulation results in different network scenarios indicate that EUSC has given much improved performance than ECHA and ‘PSO based protocol’ in terms of number of clusters formed during each round, network lifetime and energy efficiency.

A Vehicular Ad-hoc Network (VANET) is an essential component of intelligent transportation systems in the building of smart cities. A VANET is a self-configure high mobile and dynamic potential wireless ad-hoc network that joins all vehicle nodes in a smart city to provide in-vehicle infotainment services to city administrators and residents. In the smart city, the On-board Unit (OBU) of each vehicle has multiple onboard sensors that are used for data collection from the surrounding environment. One of the main issues in VANET is energy efficiency and balance because the small onboard sensors can’t be quickly recharged once installed on On-board Units (OBUs). Moreover, conserving energy stands out as a crucial challenge in VANET which is primarily contingent on the selection of Cluster Heads (CH) and the adopted packet routing strategy. To address this issue, this paper proposes distance and energy-aware clustering algorithms named SOMNNDP, which use a Self-Organizing Map Neural Network (SOMNN) machine learning technique to perform faster multi-hop data dissemination. Individual Euclidean distances and residual node energy are considered as mobility parameters throughout the cluster routing process to improve and balance the energy consumption among the participating vehicle nodes. This maximizes the lifetime of VANET by ensuring that all intermediate vehicle nodes use energy at approximately the same rate. Simulation findings demonstrate that SOMNNDP improves Quality of Service (QoS) better and consumes 17% and 14% less energy during cluster routing than distance and energy-aware variation of K-Means (KM) and Fuzzy C-Means (FCM) called KMDP and FCMDP respectively.

Achieving reliable routing is the primary concern in the Mobile Ad-hoc Network (MANET) due to dynamic topology and lack of centralized coordination. Among all protocols, the Cluster Based Routing Protocol (CBRP) is proved as an energy efficient routing protocol. In CBRP, selecting a suitable Cluster Head (CH) leads to enhanced network life time. Electing CH by considering security is one of the challenging tasks in CBRP. If elected node is malicious then attack such as routing disruption leads to data transmission failure. In order to avoid such attacks, a trustable node needs to be elected as CH for reliable routing. Existing CH election algorithms consider either trust or weight of the node as a factor to elect CH. Hence this paper proposes a Stable Trust-based Clustering Algorithm (STCA) in which both trust and weight of the node are considered for CH election. The proposed STCA allows only trustable nodes for weight calculation. This reduces computation cost in CH election. The proposed algorithm is simulated in NS3 and found to give better results in terms of number of clusters formed and lifetime of the CH.

Objective: To improve IDS strategy with high detection accuracy and reduce the power consumption of the nodes in MANET. Methods: There are several intrusion detection systems are developed. In order to increase the performance of IDS, Bayesian Correlated Equilibrium based IDS which incorporates two main processes namely, Cluster Head selection and Hybrid IDS for MANET is proposed. The game theory is also used to increase the detection accuracy of IDS. Findings: Mobile Ad-hoc Network (MANET) is an autonomous system that consists of battery powered mobile nodes. MANETs are prone to several attacks as they are continuously self configuring and infrastructure less. As the nodes are mobile, they are susceptible to intrusions. The Intrusion Detection System has issues of heavy traffic related to IDS in the network, which causes congestion. It also leads to high energy consumption among the nodes. So designing an efficient MANET should have certain number of goals such as effective intrusion detection, light traffic and low energy consumption and power loss. Many Intrusion detection schemes were proposed that normally incurs power loss in the node as there is a need for continuous monitoring. Application/Improvements: To increase detection accuracy, decrease power consumption and the IDS traffic Bayesian Correlated Equilibrium based IDS for MANET is presented.

Sensor nodes are randomly deployed to perform specific area monitoring in geographical region and temporal space. The network connectivity maintenance is a major requirement for accurate event detection with minimum energy consumption. To minimize the energy consumption, various clustering algorithms have been evolved in research studies. But, they failed to consider the other performance parameters such as quality of service constraints and the performance level. The initialization of nodes nearer to the base station (BS) as relay nodes reduces the number of relay node participation and increases the performance. This paper proposes the novel ant colony meta-heuristic based unequal clustering for the novel cluster head (CH) selection. The data fusion from the CH node to the intermediate node called Rendezvous node reduces the message transmissions and hence the energy consumed by the nodes is minimum. The neighbor finding phase and the link maintenance through the Meta-Heuristic Ant Colony Optimization approach selects the optimal path between the nodes which increases the packets delivered to the destination. The population initialization requires more time at this stage. Hence, the Haversine distance is estimated among the nodes which also reduces the dimensionality of the message transmission among the nodes. The prediction of optimal path and the CH selection using Ant Colony Optimization Meta-Heuristic and unequal clustering reduces the energy consumption effectively. The comparative analysis of proposed Meta-Heuristic Ant Colony Optimization based Unequal Clustering with the existing unequal clustering approaches on the basis of various performance parameters such as Packet Delivery Ratio, number of packets sent to the BS, energy consumption, residual energy and the percentage of dead nodes shows the effectiveness of proposed work in WSN applications.

Power control algorithms for mobile ad hoc networks

SummaryThe arbitrary distribution of sensor nodes and irregularity of the routing path led to unordered data, which is complex to handle in a wireless sensor network (WSN). To increase WSN lifetime, data aggregation models are developed to minimize energy consumption or ease the computational burden of nodes. The compressive sensing (CS) provides a new technique for prolonging the WSN lifetime. A hybrid optimized model is devised for cluster head (CH) selection and CS‐based data aggregation in WSN. The method aids to balance the energy amidst different nodes and elevated the lifetime of the network. The hybrid golden circle inspired optimization (HGCIO) is considered for cluster head (CH) selection, which aids in selecting the CH. The CH selection is done based on fitness functions like distance, energy, link quality, and delay. The routing is implemented with HGCIO to transmit the data projections using the CH to sink and evenly disperse the energy amidst various nodes. After that, compressive sensing is implemented with the Bayesian linear model. The convolutional neural network‐long short term memory (CNN‐LSTM) is employed for the data aggregation process. The proposed HGCIO‐based CNN‐LSTM provided the finest efficiency with a delay of 0.156 s, an energy of 0.353 J, a prediction error of 0.044, and a packet delivery ratio (PDR) of 76.309%.

A vehicular adhoc network (VANET) is a mobile adhoc network in which moving road vehicles are network nodes. The major problem faced in VANET is transmitting the safety message or an ALERT message between the vehicles to avoid collisions. The large number of vehicles moving in a particular area will cause the data congestion that results in a long delay on delivering the messages. Clustering the vehicles into groups is an efficient approach to broadcast the messages with a less delay and high delivering ratio. The performance of the clusters is greatly influenced by the selection of Cluster Heads (CHs). In this paper, the formation of clusters and cluster head selection is formulated as optimization problem in order to maximize the efficiency of the network energy and link quality. The formulated problem has been solved using two approaches: Density based Clustering and the cluster heads selection using Differential Evolution (DE) Algorithm. By combining these approaches the safety or Alert messages will be transmitted easily to all the vehicles by dynamically adapting transmission power and contention window size. The performance of the proposed ESMBS protocol is compared and evaluated against the existing AdvB and CBAPA protocols. The proposed scheme can control various performance metrics such as the collision, packet delivery ratio, packet delay ratio, latency, transmission time and throughput. The proposed scheme broadcasts the alert or safety messages by reducing the probability of collisions.

Many network models are too complex to readily identify which structural aspects of a network are most influential on robustness. To analyze the dynamics and robustness of a network, many of the protocol details can be reduced to a graph theory representation of nodes, links and link weights. Our method uses the spectral analysis of the Laplacian matrix to decouple the interactions between nodes to analyze the robustness of a wireless mobile ad hoc network (MANET) with a time-varying wireless channel. This spectral analysis and the resulting algebraic connectivity can be used to determine how robust a network is, where the weak links are, and how to best increase overall performance of a network. Using a simulation of wireless devices in a MANET with a time-varying channel, we show that robustness is a function of time, that nodes become coupled and decoupled as the structure of the network changes and that any robustness analysis is more complete when more than a single Eigen value is evaluated.

In this paper, we are going to evaluate various wireless network security related issues and how do they affect the quality of service of a wireless network and Mobile AdHoc Networks(MANETs). The time systems are increasingly required Getting educated more and more. Systems are simple Drastically converting the structure into more functional and dynamic. Computer networks have undergone a major move from cable to wireless A recent development has been networks and fast wireless infrastructure. MANET has appeared between many other cellular networks. Why? Why? dynamic topology without any centralization, conventional path MANETs do not comply with protocols and authentication systems. These MANETs are responsive to a lot of people It is not feasible in other networks to attack and participate in disruptive operations. A Wireless Network can be a very vulnerable entity and is always susceptible to various types of attacks and attackers, we are going to discuss a few of these attack and how do they affect the overall network performance, finally we are going to evaluate some of the solutions offered and how they improve the network.

In this paper, we deal with congestion control for multi-flow traffic in wireless mobile ad-hoc networks (MANET). For simulations, we used ns-3 open source network simulator considering Optimized Link State Routing (OLSR) routing protocol. We present the MANET performance considering random waypoint mobility model for different number of nodes and different area sizes, by sending multi-flow traffic in the network. We found that coupling congestion control mechanisms between multi-flows have problems in some cases.

Problem statement: A Mobile Ad-Hoc Networks (MANETs) operate in environments without infrastructures with an undefined network size. Most routing protocols of Mobile Ad-hoc Networks (MANETs) were studied using open space models where nodes were able to move throughput the entire simulation area. However, a more realistic topology should account for restricted mobility of nodes, such as in an urban city setting where there may be concentrations of nodes within specific areas (such as within buildings) and low density of nodes in other areas (such as in parks and roadways). Consequently, the simulation area should be partitioned into smaller sub-areas with varying densities to model such topologies, called spare/dense topologies. Approach: This study characterized the effect of spare/dense topologies on MANET routing performance and proposes an extension for an existing routing protocol to work in such topologies. Results: The proposed protocol improved the performance of MANETs by reducing the communication overhead incurred during the routing processes by implementing a new broadcast algorithm. The proposed broadcast algorithm was based on the density and connectivity of the nodes and not just the number of nodes. Conclusion: Compared with simple flooding, the proposed algorithm can improve the saved broadcast up to 50% without affecting reach ability, even under conditions of high mobility and density.

In this paper, we develop a Markov Chain model for stochastic routing in wireless mobile ad hoc networks (MANETs). We show that using stochastic routing technique the average energy efficiency of the network improves considerably. Besides, the protocol will also secure the data flow in the network as the random data forwarding paths from source to destination will make it difficult for an intruder to intercept, hijack, and jam the data. The intruder in this case will have to listen to all possible paths from the source to the destination. Simulation studies show that our proposed protocol achieves significant performance gains in terms of energy consumption, throughput, delay, and security of the data transmission in MANETs.