Search

With the increasing use of mobiles in the workplace, companies need a strict yet flexible security framework to balance risk and trust. This need has led to the expansion and rapid growth of company security technologies for mobility. Existing application mechanisms cannot precisely cover the diverse security policies of enterprise applications. However, the companies must know in which technologies they need to invest. It also needs to know whether it should rely on a single technology, a combination of technologies or adopt a unified approach. MDM (Mobile Device Management) and MAM (Mobile Application Management) are the best-known existing applications in this field. In this article, an analysis of the two most widely used mobile ecosystem management tools was done from a security point of view. In addition, a new approach that strengthens the security part of the MAM application and supports dynamic policies was proposed. The proposed mechanism is based on a set of artifacts and mobile agents as well as block chain technology to guarantee strong security during interactions between the mobile host and the mobile enterprise. The experimental results showed that this approach significantly improves the efficiency of the MAM application.

Wireless sensor network (WSN) is an applied technology widely used in various areas. According to the WSN limitations, they usually face many types of attacks. The sinkhole is the most popular and dangerous attack in the routing of WSN. There are many approaches to counter sinkhole attacks in the literature. The mobile agent methods generate better results in facing sinkhole attacks and overcoming the WSN limitations. In this paper, we present a new mobile agent-based method that applies the trust value of each sensor to detect and prevent sinkhole attacks. We compute the trust values to inform the sensor nodes about their neighbors' reputations. As shown in the experiments, the proposed method generates better results in packet loss ratio. It also fixes the security flaws of previous works and reduces the agents' overhead in the network compared to previous methods. [JJCIT 2021; 7(4.000): 391-405]

In recent research developments, the application of mobile agents (MAs) has attracted extensive research in wireless sensor networks (WSNs) due to the unique benefits it offers, such as energy conservation, network bandwidth saving, and flexibility of open usage for various WSN applications. The majority of the proposed research ideas on dynamic itinerary planning agent-based algorithms are efficient when dealing with node failure as a result of energy depletion. However, they generate inefficient groups for MAs itineraries, which introduces a delay in broadcasting data return back to the sink node, and they do not consider the expanding size of the MAs during moving towards a sequence of related nodes. In order to rectify these research issues, we propose a new Graph-based Dynamic Multi-Mobile Agent Itinerary Planning approach (GDMIP). GDMIP works with "Directed Acyclic Graph" (DAG) techniques and distributes sensor nodes into various and efficient group-based shortest-identified routes, which cover all nodes in the network using intuitionistic fuzzy sets. MAs are restricted from moving in the predefined path and routes and are responsible for collecting data from the assigned groups. The experimental results of our proposed work show the effectiveness and expediency compared to the published approaches. Therefore, our proposed algorithm is more energy efficient and effective for task delay (time). [ABSTRACT FROM AUTHOR]

Recently, the Internet of Things (IoT) has emerged as an important way to connect diverse physical devices to the internet. The IoT paves the way for a slew of new cutting-edge applications. Despite the prospective benefits and many security solutions offered in the literature, the security of IoT networks remains a critical concern, considering the massive amount of data generated and transmitted. The resource-constrained, mobile, and heterogeneous nature of the IoT makes it increasingly challenging to preserve security in routing protocols, such as the routing protocol for low-power and lossy networks (RPL). RPL does not offer good protection against routing attacks, such as rank, Sybil, and sinkhole attacks. Therefore, to augment the security of RPL, this article proposes the energy-efficient multi-mobile agent-based trust framework for RPL (MMTM-RPL). The goal of MMTM-RPL is to mitigate internal attacks in IoT-based wireless sensor networks using fog layer capabilities. MMTM-RPL mitigates rank, Sybil, and sinkhole attacks while minimizing energy and message overheads by 25–30% due to the use of mobile agents and dynamic itineraries. MMTM-RPL enhances the security of RPL and improves network lifetime (by 25–30% or more) and the detection rate (by 10% or more) compared to state-of-the-art approaches, namely, DCTM-RPL, RBAM-IoT, RPL-MRC, and DSH-RPL. [ABSTRACT FROM AUTHOR]

While robotics have been widely used in many agricultural practices such as harvesting, seeding, cattle monitoring, etc., aquaculture farming is an important, fast-growing sector of agriculture that has not seen significant adoption of advanced technologies such as robotics and the Internet of Things (IoT). In particular, dissolved oxygen (DO) monitoring, a practice in pond aquaculture essential to the health of the fish crops, remains labor-intensive and time-consuming. The Hybrid Aerial Underwater robotiCs System (HAUCS) is an IoT framework that aims to bring transformative changes to pond aquaculture. This paper focuses on the latest development in the HAUCS mobile sensing platform and field deployment. To address some shortcomings with the current implementation, the development of a novel rigid Kirigami-based robotic extension subsystem that can expand the functionality of the HAUCS platform is also being discussed. [ABSTRACT FROM AUTHOR]

Malware used in advanced persistent threats often establish a covert channel. By means of such a channel, the malware can communicate with external Command & Control servers or send classified data to a server controlled by the attacker. In military networks, these covert transmissions are a security problem with significant impact on the success of a military operation. Mobile agents in combination with machine learning are particularly suitable to detect and mitigate these type of attacks. However, a mobile agent needs to be trained before its deployment. In this paper, a concept is defined how federated learning can be used to train the mobile agents in tactical networks if the training data is distributed on the nodes of a tactical network. Furthermore, we propose an algorithm to select the nodes that are involved in the training. The proposed concepts and methods are evaluated regarding their efficiency. The evaluation considers in particular federated learning in the inter-organizational tactical networks because multinational armed forces are often involved in modern military operations. [ABSTRACT FROM AUTHOR]

Road traffic is drastically increasing in big cities around the world. In order to enable a flexible management of this traffic, Intelligent Transportation System (ITS) solutions are relying on emergent ubiquitous, mobile, and communication technologies, particularly to intelligently deal with the limited capacities of the existing road infrastructures. While intelligence is left to the autonomous and connected vehicles as well as to the ITS, the road infrastructure has been mostly playing a passive role (as a source of data). Road signage, in particular, are in best cases dynamic but do not play an active role in monitoring traffic and incidents. We propose in this paper to build Smart Road Signs (SRS) that can collaborate with Connected Vehicles in order to monitor traffic and warn drivers about any incident or danger. Our SRSs are meant to operate autonomously in order to detect road traffic problems, share appropriate information with vehicles in the vicinity, and display relevant messages based on the ongoing contextual situation. To meet our goals, we rely on Multi-Agent Systems to design SRSs as proactive components in the ITS landscape. We also rely on agent mobility in order to strengthen the collaboration with the connected vehicles. [ABSTRACT FROM AUTHOR]

Currently, Scientists are working on smart cities for providing artificial intelligence based smart facilities and services that can tackle different problems raised by rapid urbanization and boom in population growth. The Internet of things is also being used with other smart technologies to provide better solutions to the environment. It is also known as a network of networks. Mobile agent technology has also gained more attention. We are using it with different internet-based services. In this research, we have proposed two models with a sustainable approach. Our first model focused on monitoring air quality which consisted of several sensors, Arduino Uno board, and Raspberry Pi 3. The Second model explores the potential of the mobile agent technique to lever the Internet of Things in the modernization and personalized services for Smart Cities.

In recent research developments, the application of mobile agents (MAs) has attracted extensive research in wireless sensor networks (WSNs) due to the unique benefits it offers, such as energy conservation, network bandwidth saving, and flexibility of open usage for various WSN applications. The majority of the proposed research ideas on dynamic itinerary planning agent-based algorithms are efficient when dealing with node failure as a result of energy depletion. However, they generate inefficient groups for MAs itineraries, which introduces a delay in broadcasting data return back to the sink node, and they do not consider the expanding size of the MAs during moving towards a sequence of related nodes. In order to rectify these research issues, we propose a new Graph-based Dynamic Multi-Mobile Agent Itinerary Planning approach (GDMIP). GDMIP works with “Directed Acyclic Graph” (DAG) techniques and distributes sensor nodes into various and efficient group-based shortest-identified routes, which cover all nodes in the network using intuitionistic fuzzy sets. MAs are restricted from moving in the predefined path and routes and are responsible for collecting data from the assigned groups. The experimental results of our proposed work show the effectiveness and expediency compared to the published approaches. Therefore, our proposed algorithm is more energy efficient and effective for task delay (time).

The mobile ad-hoc network (MANET) is a special mobile network that has self-configuration and self-establish abilities to communicate conveniently. MANET is forming mobile devices such as mobile phones, personal digital assistants (PDAs), laptops, etc. As a result of the rapid, flexibility, and facilitate in communication, nowadays, MANET has revolutionized many real-life applications, ranging from smart agriculture and smart cities to forest fire detection systems, and expected to have vital contributions into the future of the Internet. However, due to the mobile nature of network nodes combined with the network architecture that without relying on central devices pre-installed such as base stations, the high-performance routing problem is one of the most significant challenges in the MANET environment. In this study, we propose a high-performance routing protocol, namely agent-based ad-hoc on-demand distance vector (A-AODV), to select the optimal route with high throughput and low latency. Through the developed routing algorithm, we explain how the suitable route with the lowest cost based on agents. To demonstrate the effectiveness of the proposed protocol, we compared A-AODV’s performance with two well-known traditional protocols on NS2. Simulation results show that A-AODV improves superior performance over the traditional protocols.

In this paper, we propose an algorithm for controlling a fleet of swarm robots that construct three-dimensional forms. The swarm robots coordinate with each other through network communication, and compose formations such as polyhedrons presented as spherical coordinates. Our control algorithm achieves communication through mobile software agents, which introduce control programs to robots that initially have no information about the formation. Mobile software agents are autonomous objects that can migrate from one robot to other robots through a communication network and can deliver control programs as they are needed. We have made our swarm robot system to mimic the behaviors of the leafcutter ants. A leafcutter ant is a typical social insect and uses pheromone for communication. In our robot control system, we have implemented ants and pheromones as mobile software agents. We call the mobile software agents that drive the mobile robots as ant agents, and call the other agents that provide communication as pheromone agents. The ant agents drive the swarm robots to locations identified by the pheromone agents. Each ant agent has only partial information. There is no need for either a central control or an agent that has the entire design of the formation. In order to diffuse the partial information among the neighboring robots, each ant agent generates pheromone agents and dispatches them to the surrounding robots. Dispatched pheromone agent looks for a proper ant agent to influence towards a desired relative location. It is the ant agent that actually drives the robot by following the guidance of the pheromone agent, and the collective actions of ant agents and pheromone agents achieve the composition of the objective formation. We have implemented a simulator based on our algorithm and conducted numerical experiments. The results demonstrate that our mobile robot control system is feasible and efficient in practice in practical situations.

In this paper, we propose an evacuation support system that provides evacuation routes in case of disasters, and verify the usefulness of the system. Current popular wireless communication infrastructure is supported by a series of base stations and one base station handles a lot of communication. Therefore, when communication base stations break down due to disasters such as an earthquake, it may become difficult for people to use their smartphones based on the Internet. When the communication infrastructure is paralyzed, people will have great difficulty collecting information about the conditions of transportation systems and about the safety of family and friends using smartphones. Our proposed system addresses this problem by using multiple kinds of mobile agents in addition to static agents on smartphones that use a mobile ad hoc network (MANET). The proposed system collects information with mobile agents and diffuses information via mobile agents so that the system is able to provide an optimized evacuation route for each user in a dynamically changing disaster environment. In this paper, we extend our previously proposed evacuation support system to consider elevation information when constructing evacuation routes. When a tsunami or a flood tide occurs, low elevations may be under water. Therefore, this revised evacuation support system helps people to move to safer places by selecting higher elevation routes when warranted by the situation.

In mobile cloud computing (MCC), data are stored and processed by more powerful computing platforms located in clouds to enhance the capability of mobile devices. Although MCC brings many benefits to users and organizations, security has become the main concern for MCC because it involves third party environment where data confidentiality is not a guarantee. To overcome this challenge, attribute-based encryption (ABE) technique, a promising cryptography method was introduced to support both data confidentiality and access control simultaneously. However, most of the ABE used single certification authority (CA) and disjoint attribute authority (AA) to verify user identity which can be a single point of failure. Therefore, a new approach was proposed in this research to deal with the single point of failure in the authority. Furthermore, the cache-based scheduling algorithm was upgraded to improve the response time of user jobs. The experimental results show that the approach performed better compared to its competitor in terms of reliability. Additionally, it significantly reduced the number of read operations compared to its counterpart.

In recent years, the number of cell phones in society has increased drastically and they are getting popular due to their computational ability and adaptability. Resource provisioning is important, but still remains NP-hard problem in mobile computational grid (MCG). Once the jobs are assigned to the MCG, the main challenge is how to identify the correct resource according to the job's requirement and use them to execute the sub-jobs. The heuristic methods such as Min-Min, Max-Min, and HEFT can be used to select appropriate resources from the MCG that is assigned for job execution. Since the computational nodes are static and mobile in nature, the performance of such heuristics is not as expected. Such heuristics suffers from low throughput and low speedup. The process of localization is used in a wireless sensor network with good results. The proposed model uses heuristics and localization process for optimizing the quality of service parameter localization, normalized speedup, and throughput in MCG, with the concept of grid nodes available in MCG. The observation shows significant improvement in the quality of service parameter localization, normalized speedup, and throughput in MCG. The proposed model HGLA and MIN-MIN, MAX-MIN, and HEFT are compared with respect to localization, speedup, and throughput. The results reveal that the proposed model shows better performance over MIN-MIN, MAX-MIN, and HEFT.

The past few decades have seen the rapid development of artificial intelligence (AI) technology in diverse industries. Inspired by the fact that an agent is the central part of AI, we combine AI with the technology of the mobile agent. A mobile agent used in wireless sensor networks (WSNs) is popular for its mobility, executability, and autonomy. To improve the intelligence of the mobile agent, we proposed a conceptual theoretical framework named iAgent, where i means intelligent, and the agent refers to the mobile agent. Four designs of iAgent are detailed. Compared with the old mobile agent, the iAgent has a learning ability, which means that it can dynamically plan the path according to the external environment in order to reduce energy consumption. Based on iAgent, we also proposed a method to determine the number of iAgents and their visiting areas in a multi-iAgent WSN environment. The extensive simulation indicates that the multi-iAgent algorithm can significantly improve the performance of the WSNs, especially in saving energy and balancing network load.

Abstract Mobile agent (MA)-based wireless sensor networks present a good alternative to the traditional client/server paradigm. Instead of sending the data gathered by each node to the sink as in client/server, MAs migrate to the sensor nodes (SNs) to collect data, thus reducing energy consumption and bandwidth usage. For MAs, to migrate among SNs, an itinerary should be planned before the migration. Many approaches have been proposed to solve the problem of itinerary planning for MAs, but all of these approaches are based on the assumption that MAs visit all SNs. This assumption, however, is inefficient because of the increasing size of the MAs after visiting each node. Also, in case of node(s) failure, as it is often the case in WSNs, the MAs may not be able to migrate among SNs. None of the proposed approaches takes into consideration the problem of fault tolerance. In this paper, we propose multi-mobile agent itinerary planning-based energy and fault aware data aggregation in wireless sensor networks (MAEF) to plan itineraries for MAs. This can be achieved by grouping nodes in clusters and planning itineraries efficiently among cluster heads (CHs) only. What is more, an alternative itinerary is planned in case of node(s) failure. The simulation result clearly shows that our novel approach performs better than the existing ones.

A mobile agent (MA) was recently proposed to provide an alternative solution for traditional data gathering in wireless sensor networks. An MA is a software component that can migrate among network nodes by following an assigned itinerary (or path). Instead of transporting data from the nodes to the processing unit (e.g., sink) for data gathering, the MA visits each node, and thus, it performs data gathering locally. The MA has two types of itinerary planning: single-agent itinerary planning (SIP) and multi-agent itinerary planning (MIP). The MIP was introduced to address the drawbacks of the SIP in terms of task duration, energy consumption, and reliability. Despite the advantages of the MIP, determining the optimal itinerary for each MA in the MIP poses a considerable challenge. Most proposed itineraries adopt a static itinerary in which the nodes to be visited by the MA are predetermined at the sink node. The distance among nodes is the only parameter that has been used to determine the itinerary of the MA. Other parameters, such as the remaining energy and a number of neighbors, have not been considered. This omission can negatively impact MA migration and result in an unsuccessful MA round-trip, particularly when the remaining energy of the node is insufficient to transfer an MA to the next hop. In this paper, a fuzzy-based MA migration approach (FuMAM) is proposed to determine appropriate itinerary for an MA by considering three parameters: distance, remaining energy, and a number of neighbors. Simulation experiments show that the FuMAM approach improves the rate of the successful MA round-trip and network lifetime. Moreover, the proposed FuMAM approach outperforms the compared algorithms in terms of energy distribution usage among nodes.

In order to mitigate the problem of data congestion, increased latency, and high-energy consumption in wireless sensor networks, mobile agent (MA) has been proven to be a viable alternative to the traditional client-server data gathering model. MA has the ability to migrate among network nodes based on an assigned itinerary, which can be formed via single itinerary planning (SIP) or multiple itinerary planning (MIP). MIP-based data gathering approach solves problems associated with SIP in terms of task duration, energy consumption, and reliability. However, the majority of the existing MIP approaches focus only on reducing energy consumption and task duration, while the event-to-sink throughput has not been considered. In this paper, a clone mobile-agent itinerary planning approach (CMIP) is proposed to reduce task duration while improving the event-to-sink throughput in real-time applications, especially when the MA is assigned to visit a large number of source nodes. Simulation results show that the CMIP approach outperforms both central location-based MIP (CL-MIP) and greatest information in greatest memory-based MIP (GIGM-MIP) in terms of reducing task duration by about 56% and 16%, respectively. Furthermore, CMIP improves the event-to-sink throughput by about 93% and 22% as compared to both CL-MIP and GIGM-MIP approaches, respectively.

In this paper, we consider the partial gathering problem of mobile agents in asynchronous unidirectional ring networks. The partial gathering problem is a generalization of the (well-investigated) total gathering problem, which requires that all the k agents distributed in the network terminate at a single node. The partial gathering problem requires, for a given positive integer g (< k) , that all the agents terminate in a configuration such that either at least g agents or no agent exists at each node. The requirement for the partial gathering problem is strictly weaker than that for the total gathering problem, and thus it is interesting to clarify the difference on the move complexity between them. In this paper, we aim to solve the partial gathering problem for agents without identifiers or any global knowledge such as the number k of agents or the number n of nodes. We consider deterministic and randomized cases. First, in the deterministic case, we show that the set of unsolvable initial configurations is the same as that for the case of agents with knowledge of k. In addition, we propose an algorithm that solves the problem from any solvable initial configuration in a total number of O (g n) moves. Next, in the randomized case, we propose an algorithm that solves the problem in a total number of O (g n) moves in expectation from any initial configuration. Note that g < k holds and agents require a total number of Ω (g n) (resp., Ω (k n)) moves to solve the partial (resp., total) gathering problem. Thus, our algorithms can solve the partial gathering problem in asymptotically optimal total number of moves without identifiers or global knowledge, and the total number of O (g n) moves is strictly smaller than that for the total gathering problem. [ABSTRACT FROM AUTHOR]

The modelling of wireless sensor networks has always given priority to energy efficiency. The implementation of mobile agent technology in integrated signal and wireless sensor networks has created an effective platform for data storage and aggregation. The distributed paradigm based on mobile agents provides many advantages over the current, widely used device paradigm for clients / data centres in wireless sensor networks. The agent-based paradigms are one of the major problems with mobile agent-based paradigms. Many sinks mitigate the problem by distributing traffic across several discharges, and reducing energy consumption at nodes and extending network service life. This paper presents an Energy-efficient multiple sink positioning algorithm to maximize average network life and limit average sensor network energy consumption. Several sinks are used here for data communication. Result of the proposed algorithm maximizes an average network life and reduces the energy consumption average. The results of the simulation shows that the Protocol proposed exceeds the end-to - end delay, energy consumption and output. [ABSTRACT FROM AUTHOR]

In this paper, we consider the uniform deployment problem of mobile agents in asynchronous unidirectional ring networks. This problem requires agents to spread uniformly in the network. In this paper, we focus on the memory space per agent required to solve the problem. We consider two problem settings. The first setting assumes that agents have no multiplicity detection, that is, agents cannot detect whether another agent is staying at the same node or not. In this case, we show that each agent requires Ω (log ⁡ n) memory space to solve the problem, where n is the number of nodes. In addition, we propose an algorithm to solve the problem with O (k + log ⁡ n) memory space per agent, where k is the number of agents. The second setting assumes that each agent is equipped with the weak multiplicity detection, that is, agents can detect whether another agent is staying at the same node or not, but cannot get any other information about the number of the agents. Then, we show that the memory space per agent can be reduced to O (log ⁡ k + log ⁡ log ⁡ n). To the best of our knowledge, this is the first research considering the effect of the multiplicity detection on memory space required to solve problems. [ABSTRACT FROM AUTHOR]

Different Distributed Intrusion Detection Systems (DIDS) based on mobile agents have been proposed in recent years to protect computer systems from intruders. Since intrusion detection systems deal with a large amount of data, keeping the best quality of features is an important task in these systems. In this paper, a novel DIDS based on the combination of Cuttlefish Optimization Algorithm (CFA) and Decision Tree (DT) is proposed. The proposed system uses an agent called Rule and Feature Generator Agent (RFGA) to generate a subset of features with corresponding rules. RFGA agent uses CFA to search for optimal subset of features, while DT is used as a measurement on the selected features. The proposed model is tested on the KDD Cup 99 dataset. The obtained results show that the proposed system gives a better performance even with a small subset of 5 features when compared with using all 41 features.

The sum of Big Data generated from different sources is increasing significantly with each passing day to extent that it is becoming challenging for traditional storage methods to store this massive amount of data. For this reason, most organizations have resolved to use third-party cloud storage to store data. Cloud storage has advanced in recent times, but it still faces numerous challenges with regard to security and privacy. This paper discusses Big Data security and privacy challenges and the minimum requirements that must be provided by future solutions. The main objective of this paper is to propose a new technical framework to control and manage Big Data security and privacy risks. A design science research methodology is used to carry out this project. The proposed framework takes advantage of Blockchain technology to provide secure storage of Big Data by managing its metadata and policies and eliminating external parties to maintain data security and privacy. Additionally, it uses mobile agent technology to take advantage of the benefits related to system performance in general. We present a prototype implementation for our proposed framework using the Ethereum Blockchain in a real data storage scenario. The empirical results and framework evaluation show that our proposed framework provides an effective solution for secure data storage in a Big Data environment.

The multi mobile agent collaboration planning model was constructed based on the mobile agent load balancing and total network energy consumption index.In order to prolong the network lifetime,the network node dormancy mechanism based on WSN network coverage was put forward,using fewer worked nodes to meet the requirements of network coverage.According to the multi mobile agent collaborative planning technical features,the multi-objective discrete social spider optimization algorithm (MDSSO) with Pareto optimal solutions was designed.The interpolation learning and exchange variations particle updating strategy was redefined,and the optimal set size was adjusted dynamically,which helps to improve the accuracy of MDSSO.Simulation results show that the proposed algorithm can quickly give the WSN multi mobile agent path planning scheme,and compared with other schemes,the network total energy consumption has reduced by 15%,and the network lifetime has increased by 23%.

A statistics states that public Wi-Fi hotspots are set to grow from 1.3 million in 2011 to 5.8 million by 2015. Due to increase in public free Wi-Fi access, userscount increases rapidly letting them to expose in vulnerable intrusion attacks. Accessing the social network and other confidential sites such as banking in public Wi-Fi, exposes the credential to the intruder. Man-in-the-middle attack plays a major role in accessing the user credential. Analysing the packets exposes the HTTP post information in the network. Capturing encrypted cookies by the man-in-the-middle can access the secure site and allows the intruder to be an authorized person. Mobile agent is a piece of code that migrates and performs actions in the host and is used to prevent intrusion. We propose a model to prevent intrusion in the wireless ad-hoc network using mobile agent. Session-Packet inspector is proposed to handle HTTP post hijacking and encrypted cookie usage by the intruder.

In this paper, we propose an evacuation support system that provides evacuation routes in case of disasters, and verify the usefulness of the system. Current popular wireless communication infrastructure is supported by a series of base stations and one base station handles a lot of communication. Therefore, when communication base stations break down due to disasters such as an earthquake, it may become difficult for people to use their smartphones based on the Internet. When the communication infrastructure is paralyzed, people will have great difficulty collecting information about the conditions of transportation systems and about the safety of family and friends using smartphones. Our proposed system addresses this problem by using multiple kinds of mobile agents in addition to static agents on smartphones that use a mobile ad hoc network (MANET). The proposed system collects information with mobile agents and diffuses information via mobile agents so that the system is able to provide an optimized evacuation route for each user in a dynamically changing disaster environment. In this paper, we extend our previously proposed evacuation support system to consider elevation information when constructing evacuation routes. When a tsunami or a flood tide occurs, low elevations may be under water. Therefore, this revised evacuation support system helps people to move to safer places by selecting higher elevation routes when warranted by the situation. [ABSTRACT FROM AUTHOR]

In this paper, we propose an algorithm for controlling a fleet of swarm robots that construct three-dimensional forms. The swarm robots coordinate with each other through network communication, and compose formations such as polyhedrons presented as spherical coordinates. Our control algorithm achieves communication through mobile software agents, which introduce control programs to robots that initially have no information about the formation. Mobile software agents are autonomous objects that can migrate from one robot to other robots through a communication network and can deliver control programs as they are needed. We have made our swarm robot system to mimic the behaviors of the leafcutter ants. A leafcutter ant is a typical social insect and uses pheromone for communication. In our robot control system, we have implemented ants and pheromones as mobile software agents. We call the mobile software agents that drive the mobile robots as ant agents, and call the other agents that provide communication as pheromone agents. The ant agents drive the swarm robots to locations identified by the pheromone agents. Each ant agent has only partial information. There is no need for either a central control or an agent that has the entire design of the formation. In order to diffuse the partial information among the neighboring robots, each ant agent generates pheromone agents and dispatches them to the surrounding robots. Dispatched pheromone agent looks for a proper ant agent to influence towards a desired relative location. It is the ant agent that actually drives the robot by following the guidance of the pheromone agent, and the collective actions of ant agents and pheromone agents achieve the composition of the objective formation. We have implemented a simulator based on our algorithm and conducted numerical experiments. The results demonstrate that our mobile robot control system is feasible and efficient in practice in practical situations. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new mechanism to improve the disadvantage of the security mechanism proposed by a scholar and then fulfill the demands of Internet of Things (IoT) to go through the decentralized environment access control functions. We also propose the date-constrained hierarchical key management scheme for mobile agents. With elliptic curve cryptosystems (ECCs) and discrete logarithms, the proposed scheme is flexible. Moreover, the duration of access for each security class is restricted with a certain authorized discrete time period. We demonstrate the mathematical derivation and arguments for our scheme and further conduct a numerical trial. The constructed scheme could meet security needs and be more space-efficient. [ABSTRACT FROM AUTHOR]

Indoor autonomous navigation refers to the perception and exploration abilities of mobile agents in unknown indoor environments with the help of various sensors. It is the basic and one of the most important functions of mobile agents. In spite of the high performance of the single-sensor navigation method, multi-sensor fusion methods still potentially improve the perception and navigation abilities of mobile agents. This work summarizes the multi-sensor fusion methods for mobile agents’ navigation by: (1) analyzing and comparing the advantages and disadvantages of a single sensor in the task of navigation; (2) introducing the mainstream technologies of multi-sensor fusion methods, including various combinations of sensors and several widely recognized multi-modal sensor datasets. Finally, we discuss the possible technique trends of multi-sensor fusion methods, especially its technique challenges in practical navigation environments.

Although multiple mobile agents(MA)collaboration can quickly and efficiently complete data aggregation in wireless sensor network,the MA carrying data packages extensively increase along with a raise in the number of data source nodes accessed by MA,which causes unbalanced energy load of sensor nodes,high energy consumption of partial source nodes,and shortened lifetime of networks.The existing related works mainly focus on the objective of decreasing total energy consumption of multiple MA,without considering that rapidly energy consumption of partial source nodes has a negative effect on networks lifetime.Therefore,discrete multi-objective optimization of particle swarm algorithm was proposed,which used the total network energy consumption and mobile agent load balancing as fitness function for the approximate optimal itinerary plan in multiple mobile agent collaboration.Furthermore,the simulation result of the proposed algorithm is better than the similar algorithm in total energy consumption and network lifetime.

Mobile agent-based applications are special type of software systems which take the advantages of mobile agents in order to provide a new beneficial paradigm to solve multiple complex problems in several fields and areas such as network management, e-commerce, e-learning, etc. Likewise, we notice lack of real applications based on this paradigm and lack of serious evaluations of their modeling approaches. Hence, this paper provides a comparative study of modeling approaches of mobile agent-based software systems. The objective is to give the reader an overview and a thorough understanding of the work that has been done and where the gaps in the research are.

A data offloading strategy for optimizing itinerary planning of MA（mobile agent）was proposed. When MA visits source nodes based on data offloading strategy，it decides whether to transfer data package via optimized offloading itinerary and MA（mobile agent）visits data source nodes via conventional itinerary. Based on considerable simulations with the representative MA itinerary planning，i.e. itinerary energy minimum for first-source-selection （IEMF），it verifies that the problem of excessive energy consumption from source nodes can be efficiently solved and the lifetime of source nodes is prolonged.

The researches about a mobile entity (called agent) on dynamic networks have attracted a lot of attention in recent years. Exploration which requires an agent to visit all the nodes in the network is one of the most fundamental problems. While the exploration of dynamic networks with complete information or with no information about network changes has been studied, an agent with partial information about the network changes has not been considered yet despite its practical importance. In this paper, we consider the exploration of dynamic networks by a single agent with partial information about network changes. To the best of our knowledge, this is the very first work to investigate the exploration problem with such partial information. As a first step in this research direction, we focus on 1-interval connected rings as dynamic networks in this paper. We assume that the single agent has partial information called the ( H , S ) view by which it always knows whether or not each of the links within H hops is available in each of the next S time steps. In this setting, we show that H + S ≥ n and S ≥ ⌈ n / 2 ⌉ (n is the size of the network) are necessary and sufficient conditions to explore 1-interval connected rings. Moreover, we investigate the upper and lower bounds of the exploration time. It is proven that the exploration time is O ( n 2 ) for ⌈ n / 2 ⌉ ≤ S < 2 H ′ − 1 , O ( n 2 / H + n H ) for S ≥ max ( ⌈ n / 2 ⌉ , 2 H ′ − 1 ) , O ( n 2 / H + n log H ) for S ≥ n − 1 , and Ω ( n 2 / H ) for any S where H ′ = min ( H , ⌊ n / 2 ⌋ ) .

A pivotal cause for the boom of Mobile Agent paradigm relies on the competence to ward off security attacks. This article surveys the prevalent attacks on the mobile agents and the agent platforms; the existing countermeasures and their curbs, catering threefold benefaction: First, to acquaint the researchers with numerous security requirements and the objectives. Second, to analyze the different detection and prevention mechanisms mitigating the security bottlenecks in Mobile Agents System. Third, to address the future security challenges. In a nutshell, this survey hands over a key to researchers who primarily target the security concerns of the mobile agent-based applications. [ABSTRACT FROM AUTHOR]

In this paper, we consider the uniform deployment problem of mobile agents in asynchronous unidirectional rings, which requires the agents to uniformly spread in the ring. The uniform deployment problem is in striking contrast to the rendezvous problem which requires the agents to meet at the same node. While rendezvous aims to break the symmetry, uniform deployment aims to attain the symmetry. It is well known that the symmetry breaking is difficult in distributed systems and the rendezvous problem cannot be solved from some initial configurations. Hence, we are interested in clarifying what difference the uniform deployment problem has on the solvability and the number of agent moves compared to the rendezvous problem. We consider two problem settings, with knowledge of k (or n ) and without knowledge of k or n where k is the number of agents and n is the number of nodes. First, we consider agents with knowledge of k (or n since k and n can be easily obtained if one of them is given). In this case, we propose two algorithms. The first algorithm solves the uniform deployment problem with termination detection. This algorithm requires O ( k log n ) memory space per agent, O ( n ) time, and O ( k n ) total moves. The second algorithm also solves the uniform deployment problem with termination detection. This algorithm reduces the memory space per agent to O ( log n ) , but uses O ( n log k ) time, and requires O ( k n ) total moves. Both algorithms are asymptotically optimal in terms of total moves since there are some initial configurations such that agents require Ω ( k n ) total moves to solve the problem. Next, we consider agents with no knowledge of k or n . In this case, we show that, when termination detection is required, there exists no algorithm to solve the uniform deployment problem. For this reason, we consider the relaxed uniform deployment problem that does not require termination detection, and we propose an algorithm to solve the relaxed uniform deployment problem. This algorithm requires O ( ( k ∕ l ) log ( n ∕ l ) ) memory space per agent, O ( n ∕ l ) time, and O ( k n ∕ l ) total moves when the initial configuration has symmetry degree l . This means that the algorithm can solve the problem more efficiently when the initial configuration has higher symmetric degree (i.e., is closer to uniform deployment). Note that all the proposed algorithms achieve uniform deployment from any initial configuration, which is a striking difference from the rendezvous problem because the rendezvous problem is not solvable from some initial configurations. [ABSTRACT FROM AUTHOR]

We investigate initial information, unbounded memory and randomization in gathering mobile agents on a grid. We construct a state machine, such that it is possible to gather, with probability 1, all configurations of its copies. This machine has initial input, unbounded memory, and is randomized. We show that no machine having any two of these capabilities but not the third, can be used to gather, with high probability, all configurations. We construct deterministic Turing Machines that are used to gather all connected configurations, and we construct deterministic finite automata that are used to gather all contractible connected configurations. [ABSTRACT FROM AUTHOR]

We introduce access management methods and their disadvantages after reviewing previous papers. On the basis of the Chinese remainder theorem (CRT), we have developed a mobile agent novel key management scheme that solves some of the defects. We demonstrate a mobile agent that can secure and collect information across different places. We also illustrate the mathematical computation of our proposed method. Moreover, our proposed method is flexible since the whole system is considered. [ABSTRACT FROM AUTHOR]

In this paper, we consider the partial gathering problem of mobile agents in asynchronous tree networks. The partial gathering problem is a generalization of the classical gathering problem, which requires that all the agents meet at the same node. The partial gathering problem requires, for a given positive integer g , that each agent should move to a node and terminate so that at least g agents should meet at each of the nodes they terminate at. The requirement for the partial gathering problem is weaker than that for the (well-investigated) classical gathering problem, and thus, we clarify the difference on the move complexity between them. We consider two multiplicity detection models: weak multiplicity detection and strong multiplicity detection models. In the weak multiplicity detection model, each agent can detect whether another agent exists at the current node or not but cannot count the exact number of the agents. In the strong multiplicity detection model, each agent can count the number of agents at the current node. In addition, we consider two token models: non-token model and removable token model. In the non-token model, agents cannot mark the nodes or the edges in any way. In the removable-token model, each agent initially leaves a token on its initial node, and agents can remove the tokens. Our contribution is as follows. First, we show that for the non-token model agents require Ω ( k n ) total moves to solve the partial gathering problem, where n is the number of nodes and k is the number of agents. Second, we consider the weak multiplicity detection and non-token model. In this model, for asymmetric trees, by a previous result agents can achieve the partial gathering in O ( k n ) total moves, which is asymptotically optimal in terms of total moves. In addition, for symmetric trees we show that there exist no algorithms to solve the partial gathering problem. Third, we consider the strong multiplicity detection and non-token model. In this model, for any trees we propose an algorithm to achieve the partial gathering in O ( k n ) total moves, which is asymptotically optimal in terms of total moves. At last, we consider the weak multiplicity detection and removable-token model. In this model, we propose an algorithm to achieve the partial gathering in O ( g n ) total moves. Note that in this model, agents require Ω ( g n ) total moves to solve the partial gathering problem. Hence, the second proposed algorithm is also asymptotically optimal in terms of total moves. [ABSTRACT FROM AUTHOR]

Wireless Sensor Network is playing a crucial role in daily life because of its distributed sensing ability in combination with wireless communication techniques and self-organising deployment approaches. To satisfy requirements of easily matching diversified dynamic sensing applications and highly heterogeneous sensor platforms from perspective of logistics, a low budget but high-efficient wireless sensor network middleware is in dire need. To maximise commercial benefits, a WSN middleware is designed in order to increase efficacy and return on investment. This paper presents a design of an inventive mobile agent-based middleware, which could optimally achieve the intensive requirements of a WSN middleware. The middleware proposed in this paper has considered resources limitation issues that are commonly addressed on normal sensor nodes, meanwhile it provides a possibility of platform independence as well as programming language independence. In addition, a mobile agentbased system can reduce network payload and dynamically adapt to environmental changes. Therefore, the middleware presented in this paper has ability of perceiving changes in operating environment and ability to automatically response to these changes. [ABSTRACT FROM AUTHOR]