Mobile Agent Routing Research Articles

A DMA-WSN Based Routing Strategy to Maximize Efficiency and Reliability in a Ship to Communicate Data on Coronavirus

Background: The Sensor Nodes (SNs) are deployed in an environment where human beings are not able to perform the tasks. Wireless Sensor Network (WSN) is used for applications in security, military surveillance, habitat monitoring, agriculture, etc. All these applications require SNs to have good battery backup so that they can perform for a long duration. Recent research shows that agent-based strategies increase the efficiency of WSN in comparison to conventional WSN in which every SN is static. During the current pandemic of Covid-19, various public resources, such as train, bus, hotels, etc., were used for isolating the Covid-19 patients. In a similar way, the ship helps to keep humans away from each other. Methods: In the current work, WSN has been deployed on a ship to monitor the health of Covid-19 patients. A 109 m long ship with 12.8 m altitude and 23 m width along with 6 decks has been considered. The SNs have been deployed on different floors of the modern ship. Six decks have been considered, and on each deck, 50 SNs have been deployed. A Drone-driven Mobile Agent (DMA) routing strategy has been proposed. DMA is a software program that moves across the network around the SNs and collects information from wearable sensors, such as body temperature, SpO2, etc. DMA is capable of aggregating and delivering the data packets to the base station for further processing. DMA performs information processing, local processing, and collaborative signaling. DMA can move randomly or in fixed locations. Results: Results have been compared with multi-sink and mobile sink strategies, which reveal that the proposed and simulated technique enhances the life span and throughput of the network to monitor Covid-19 patients effectively. Conclusion: Results revealed the proposed technique to enhance the lifetime (DMA-fixed: 11633 rounds and DMA-random: 11740 rounds) and throughput (DMA-fixed: 148788 packets sent and DMA-random: 150008 packets sent) of the network.

Advanced energy efficient pegasis based routing protocol for IoT applications

The Scientific betterments in Wireless Sensor Networks (WSNs) technology have paved the way for the advancement of lower sized, reduced-cost, and highly-powered sensor nodes. The sensor nodes are consistently expected to work with limited power batteries, and their energy is the most precious asset in a WSN, proper usage of the total energy to perpetuate the Network's lifetime is the primary constraint and objective of the majority of the research works. As energy conservation and prolonging of network-lifetime have become a critical issue, a novel protocol for WSN based on an Advanced Fixed Path and Mobile Base Station energy-efficient PEGASIS based routing protocol is proposed in this research work. The proposed method focuses on the base station's specified mobility with a multiple-chain model to attain small size chains and reduce the single leader node load that directly affect the Network's energy conservation and lifetime. The experimental results based on average energy, residual energy, consumed energy, dead nodes, and alive nodes reflect the proposed method's efficiency to fulfill the above-said objectives. The proposed method is also compared with three current routing protocols, i.e., Energy Efficient Routing Algorithm with Mobile Sink Support for WSNs (EERCCSM), Cluster-Chain Mobile Agent Routing (CCMAR), and Energy-efficient Cluster-based Dynamic Routing Algorithm (ECDRA). This novelty and advancement of the base station will open new horizons for getting it placed much closer to the cluster leader to prolong Network's lifetime to a great extent in the future.

MINDS: Mobile Agent Itinerary Planning Using Named Data Networking in Wireless Sensor Networks

Mobile agents have the potential to offer benefits, as they are able to either independently or cooperatively move throughout networks and collect/aggregate sensory data samples. They are programmed to autonomously move and visit sensory data stations through optimal paths, which are established according to the application requirements. However, mobile agent routing protocols still suffer heavy computation/communication overheads, lack of route planning accuracy and long-delay mobile agent migrations. For this, mobile agent route planning protocols aim to find the best-fitted paths for completing missions (e.g., data collection) with minimised delay, maximised performance and minimised transmitted traffic. This article proposes a mobile agent route planning protocol for sensory data collection called MINDS. The key goal of this MINDS is to reduce network traffic, maximise data robustness and minimise delay at the same time. This protocol utilises the Hamming distance technique to partition a sensor network into a number of data-centric clusters. In turn, a named data networking approach is used to form the cluster-heads as a data-centric, tree-based communication infrastructure. The mobile agents utilise a modified version of the Depth-First Search algorithm to move through the tree infrastructure according to a hop-count-aware fashion. As the simulation results show, MINDS reduces path length, reduces network traffic and increases data robustness as compared with two conventional benchmarks (ZMA and TBID) in dense and large wireless sensor networks.

Energy Efficient Routing Algorithm with Mobile Sink Support for Wireless Sensor Networks.

Recently, wireless sensor network (WSN) has drawn wide attention. It can be viewed as a network with lots of sensors that are autonomously organized and cooperate with each other to collect, process, and transmit data around targets to some remote administrative center. As such, sensors may be deployed in harsh environments where it is impossible for battery replacement. Therefore, energy efficient routing is crucial for applications that introduce WSNs. In this paper, we present an energy efficient routing schema combined with clustering and sink mobility technology. We first divide the whole sensor field into sectors and each sector elects a Cluster Head (CH) by calculating its members’ weight. Member nodes calculate energy consumption of different routing paths to choose the optimal scenario. Then CHs are connected into a chain using the greedy algorithm for intercluster communication. Simulation results prove the presented schema outperforms some similar work such as Cluster-Chain Mobile Agent Routing (CCMAR) and Energy-efficient Cluster-based Dynamic Routing Algorithm (ECDRA). Additionally, we explore the influence of different network parameters on the performance of the network and further enhance its performance.

Cluster-chain mobile agent routing algorithm for efficient data aggregation in wireless sensor network

The sensor nodes have limited sensing, computation, communication capabilities and are mostly operated by batteries in a harsh environment with non-replenishable power sources. These restrictions make the sensor network prone to failures because most of the energy is spent on data transmission, sensing, and computing. Many applications such as habitat monitoring, military surveillance and forest fire detection expect the sensor nodes to last for a long time because they operate human unattended. Therefore, the major challenges in designing a wireless sensor network (WSN) are energy conservation, reducing data transmission delay and improving the network lifetime. In this context, data aggregation is an intelligent technique used in WSN, wherein the data from disparate sources are accumulated at intermediate nodes, thereby reducing the number of packets to be sent to the sink. Literature study shows that various routing algorithms are used to perform data aggregation based on the network topology. In order to provide an improved performance amongst the existing, a routing algorithm called cluster-chain mobile agent routing (CCMAR) is proposed in this work. It makes full use of the advantages of both low energy adaptive clustering hierarchy (LEACH) and power-efficient gathering in sensor information systems (PEGASIS). CCMAR divides the WSN into a few clusters and runs in two phases.The proposed system is simulated and evaluated for the performance metrics such as energy consumption, transmission delay and network lifetime. The results demonstrate that the proposed CCMAR outperforms LEACH, PEGASIS and other similar routing algorithm, energy efficient cluster-chain based protocol.

Research on the Algorithm of Multi Sensor Data Fusion Based on Simulated Annealing Algorithm and Genetic Algorithm

We can know from the analysis of the data fusion model of wireless sensor network that data redundancy exists in the data transmission process because of the limitation of computing capability and communication capability of sensor nodes deployed in a cross and repeated manner. Therefore, we need to conduct research on data fusion technology to reduce or remove redundant and invalid data to save communication energy consumption and improve efficiency. This paper conducts research on a type of WSN data fusion algorithm of simulated annealing algorithm on the basis of the merits of global search of genetic algorithm and local search of simulated annealing algorithm. This algorithm can quickly locate the optimal sensor node sequence of mobile agent routing and achieve data fusion with good efficiency. Finally, this paper conduct simulation analysis and verification and the results indicate the validity of this algorithm.

A Mobile Agent Routing Protocol for Data Aggregation in Wireless Sensor Networks

Mobile agent data aggregation routing forwards mobile agents in wireless sensor network to collect and aggregate data. The key objective of data aggregation routing is to maximise the number of collected data samples at the same time as minimising network resource consumption and data collection delay. This paper proposes a mobile agent routing protocol, called zone-based mobile agent aggregation. This protocol utilises a bottom-up mobile agent migration scheme in which the mobile agents start their journeys from the centre of the event regions to the sink aiming to reduce the MA itinerary cost and delay and increase data aggregation routing accuracy. In addition, the proposed protocol reduces the impact of network architecture, event source distribution model and/or data heterogeneity on the performance of data aggregation routing.

Agent Based Predictive Data Collection in Opportunistic Wireless Sensor Network

Abstract Opportunistic wireless sensor networks have significant applications like remote monitoring where node density is usually low than average. The traditional deployment of sensor networks has larger density, confirmed communication links and multiple routing paths. This does not apply to opportunistic networks. Due to sensing nodes constraints and sparse connectivity, the data collection in OWSN is a difficult task. Mobile agents can be injected into the network for performing network exploration to collect metadata of nodes. Ant-AODV routing protocol provides least overhead in mobile agent routing. Based on the metadata a predictive model can be built to find the probable contact time and location of the mobile nodes and sink in OWSN. This paper simulates an agent based predictive data collection algorithm (PLA). The simulation results are then compared with other opportunistic algorithms and the data collection performance improves almost by 33.2%.

NETWORKING PARADIGM FOR DISTRIBUTED SENSOR NETWORKS

An increasing number of distributed sensor networks are being deployed in a wide spectrum of scenarios for both military and civilian applications. The design of such systems requires the integration of many methods for solving various problems ranging from sensor deployment, through data communication, information fusion to environmental inference and hypothesis testing. This paper is focused on the network aspects in support of data communication services. We present some recent developments in networking techniques for multiple sensor systems in three topics: efficient mobile agent routing in mobile agent-based distributed sensor networks, bandwidth aggregation using multiple paths in wide-area wireline networks, and connectivity enhancement using node movements in small-area wireless mobile ad-hoc networks.

Wireless Sensor Network Mobile Agent Routing Based on the Improved Ant Colony Algorithm

This paper proposes a new wireless sensor routing algorithm by combining the ant colony algorithm with the mobile agent technology. This algorithm considers the distance and path energy overhead among nodes and residual node energy, equalizes the energy overhead in the network, improves the update rule of the ant colony information elements and speeds up convergence of the ant colony algorithm to get the optimal values. The simulation results indicate that this algorithm can improve the globalization and convergence speed, effectively reduce redundant data transmission and communication overhead, extend the network lifecycle and be very suitable for a large-scale wireless sensor network compared to other mobile agent routing algorithms.

Mobile Agent routing algorithm for WSN based on Q learning hybrid with ant colony optimization

In view of mobile Agent routing problem in Wireless Sensor Networks( WSN), a mobile Agent routing algorithm for WSN based on Q learning hybrid with ant colony optimization was proposed. A new path choosing probability model was introduced and the optimal path was efficiently maintained in the algorithm. The simulation results show that the mobile Agent routing efficiency is highly improved and delay requirements in multiple tasks are fulfilled, the reliability of the optimal path is enhanced, and network energy consumption is reduced.

Application Research of Improved Ant Colony Algorithm in Hybrid Mobile Agent Routing

Mobile agent routing essentially is a multi-constraint optimization problem, for Ant Colony algorithm for global search capability is weak, the feedback information of the system does not use and has the problem of low efficiency of finding exact solutions, propose an improved Ant Colony Algorithm for WSN mobile agent routing. This algorithm takes full use of the wireless sensor node energy, the direction of ants is determined according to the residual energy and the distance of nodes, quickly find the global optimal solution for mobile agent route. Simulation results show that the algorithm can find optimal mobile agent route in a relatively short time, relative to other routing algorithms, reducing network latency and average energy consumption, effectively alleviate network congestion, and extend the network lifetime.

Research of Hybrid Mobile Agent Routing in Wireless Sensor Network

The mobile agent route is essentially a multi-constraint optimization problem, Genetic Algorithms has fast random global search ability, but the feedback information of the system does not use and has the problem of low efficiency of finding exact solutions, propose a genetic hybrid ant colony algorithm for WSN mobile agent route. Use of the fast random global search capabilities of genetic algorithm to find better solutions, then the better solution replaced by the initial pheromone of the ant colony algorithm, finally use the advantages of convergence speed of ant colony algorithm to find the global optimal solution for mobile agent route. Simulation results show that the algorithm can find optimal mobile agent route in a relatively short time, relative to other routing algorithms, reducing network latency and average energy consumption, improving the speed and efficiency of data transfer.

Efficient Routing of Mobile Agents in a Stochastic Network

Mobile agents are autonomous programs that may be dispatched through computer networks. Using a mobile agent is a potentially efficient method to perform transactions and retrieve information in networks. Unknown congestion in a network causes uncertainty in the routing times of mobile agents so the routing of mobile agents cannot rely solely on the average travel time. In this paper we deal with a given stochastic network in which the mobile agent routing time is a random variable. Given pre-specified values R and PR, the objective is to find the path with the minimum expected time under the constraint that the probability that the path time is less than R is at least PR. We show that this problem is NP-hard, and construct an exact pseudo-polynomial algorithm and an ^approximation algorithm (FPTAS) for the problem. Index Terms—Agent-based architecture, fast routing algo­ rithm, FPTAS, stochastic routing. I. In t r o d u c t i o n

Wireless Sensor Network Mobile Agent routing based on the Improved Ant Colony Algorithm

Wireless Sensor Network Mobile Agent routing based on the Improved Ant Colony Algorithm

A Mobile Agent Routing Algorithm in Dual-Channel Wireless Sensor Network

A mobile agent routing algorithm (MARA) is presented in this paper, and then based on the dual-channel communication model, the two-layer network combination optimization strategy is also proposed. Since this strategy deals with the collision between packets and the multicast suppression in channel competitive process well, the blocking probability of network and the error rate of packet transmission can be cut down by utilizing this strategy. Furthermore, a restore rule for the failure optimal route is presented too. By using this rule, the optimal route can restore quickly in the local of fail nodes and most of the information of original optimal route can be reserved. Compared with other existing algorithms like ant colony optimization-based dynamic energy-efficient mobile agent routing algorithm (ADEEMA) and mobile agent-based wireless sensor network (MAWSN), simulation results show that MARA performs better in improving the success rate of packet transmission and cutting down the delay of communication. The success rate of packet transmission is improved 15%. Simultaneously, this algorithm can keep the ant agents away from the nodes with less residual energy in searching for the optimal route. This way can make the energy of each nodes on the optimal route overall decline and hence improve the lifetime of network.

An Improved FPTAS for Mobile Agent Routing with Time Constraints

Camponogara and Shima (2010) developed an e-approximation algorithm (FPTAS) for the mobile agent routing problem in which a benefit function determines how visits to different sites contribute to the agent's mission. The benefit is to be maximized under a time constraint. They reduced the problem to the constrained longest-path problem in a graph. In this note we present a modified FPTAS that improves on their result by a factor of () () log log / nh b b, where b and b are an upper bound and a lower bound on the maximum benefit, respectively, n is the number of nodes, and h is the length of the longest path (in hops) in the graph.

A Survey of Identity-based Signcryption

Signcryption is a cryptographic primitive that fulfills both the functions of digital signature and public key encryption simultaneously, at a cost significantly lower than that required by the traditional signature-then-encryption approach. Signcryption has found many applications, such as electronic transaction protocol, mobile agent protocol, key management, and routing protocol. In this article, the state-of-the-art of identity-based signcryption (IBSC) is surveyed. We examine the security model of IBSC. We survey the existing IBSC schemes and compare their security properties and efficiency. IBSC with special properties and identity-based hybrid signcryption are investigated. Some possible future work is also pointed out.

A Self-adapted Anycast Routing Algorithm Based on Mobile Agent in Wireless Sensor Network

To reduce the transmissions among sensor nodes and prolong the lifecycle of the wireless sensor network, the immune theory and anycast technique were brought into the mobile agent routing mechanism, and an immune-based MA anycast routing algorithm was put forward. In this algorithm , the diversity and self-adaptation characters of artificial immune system were used to find out the optimal data source searching order , and then the anycast strategy was used to select a node in multiple sensing nodes of a data source. MA migrated in the nodes which was satisfied the energy conditions. The MA a nycast routing mechanism was used to balance the energy consumption of sensors. Simulation results show that the proposed algorithm can reduce the energy consumption and prolong the lifetime of WSN effectively.

Mobile Agent Routing with Time Constraints: A Resource Constrained Longest-Path Approach

Mobile agent technology advocates the mobility of code rather than the transfer of data. As data is found in several sites, a mobile agent has to plan an itinerary to visit several sites where it collects resources to accomplish its mission. This gives rise to the mobile-agent itinerary problem (MIP) which seeks a route maximizing overall benefit from the resources while meeting a deadline. This paper formalizes MIP and develops a reduction to the resource constrained longest-path problem (CLPP) in acyclic graphs. A dynamic programming (DP) algorithm was designed to produce a family of optimal routes, allowing a mobile agent to dynamically revise its route. A fully-polynomial approximation scheme was developed to reduce the pseudo-polynomial running time of DP, whereby the distance to the optimal is controlled by a parameter and the running time is limited by a polynomial on problem size and 1/ . The paper reports results from experiments assessing the performance of the algorithms and discusses extensions to handle non-additive objectives, non-additive constraints, and probabilistic resource constraints.