Search

A mobile agent, which is an autonomous device navigating in a graph, has to explore a given graph by visiting all of its nodes. We adopt the (arguably) weakest possible model of such a device: a deterministic memoryless automaton (DMA), i.e., a deterministic automaton with a single state. As expected, such a weak machine is incapable of exploring many graphs without marking nodes. Hence we allow the agent to use identical movable pebbles that can be dropped on nodes or picked from them. It turns out that this marking capability significantly enhances the exploration power of the agent. Our goal is to study how the availability of pebbles impacts the class of graphs that a DMA can explore. We first concentrate on finite graphs and show that any finite tree can be explored by a DMA without pebbles but there exist (small) finite graphs that cannot be explored by a DMA without pebbles. Then we turn attention to infinite graphs and fully characterize the class of infinite trees that can be explored by a DMA without pebbles. We also define a large class of infinite trees that can be explored by a DMA with finitely many pebbles. It turns out that many of these trees cannot be explored by a DMA without pebbles. On the other hand, we show a large class of infinite trees that cannot be explored by a DMA with finitely many pebbles. Thus, availability of pebbles yields a strict hierarchy of difficulty of exploration of infinite graphs by a DMA, and this hierarchy is strict even for the class of infinite trees: some trees can be explored without pebbles, some trees can be explored with finitely many pebbles but not without pebbles, and some trees require infinitely many pebbles. Finally, we consider exploration by a DMA with infinitely many pebbles. It turns out that all infinite trees can be explored by a DMA with infinitely many pebbles. By contrast, we construct infinite graphs that cannot be explored by any DMA, even with infinitely many pebbles. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSN) are composed of small sensor nodes that either transmit their sensed data to the sink node directly or transmit it to its respective cluster head, which then transmits it to the sink node. However, this consumes a lot of network bandwidth and energy from the constrained sensor nodes. To address these constraints, Mobile Agents (MA) paradigm can be used in WSNs, which may lead to better energy and bandwidth conservation. When a single mobile agent is insufficient to complete a task, multiple mobile agents can be deployed to perform in parallel and reduce network latency. The set of sensor nodes and their sequence that MAs must migrate to complete a task is called an itinerary. The planning of the itinerary is the most prominent and significant issue related to the MA-based system, including the determination of an appropriate number of MAs to be dispatched, determining the set of sensor nodes and their sequence to be visited by MAs. This paper proposes a fuzzy-based algorithm to partition Wireless Sensor Networks into a set of sensor nodes, called domains, for enhancing the efficiency of the WSN in terms of its prolonged operation. Experimental evaluations are conducted to compare the proposed algorithm with benchmarked algorithms. The paper suggests that the proposed algorithm's integration with MA-based systems can enhance their performance and prolong the WSN's lifetime. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of resilient vector consensus for a group of dynamic agents against mobile malicious attacks. As real networks often operate under random environment and noises, we approach this problem by considering general random dynamic networks with weighted directed topologies. We propose three types of mobile attack models, which differ in the timing of moving of attackers and the capability of detecting such moving. By employing distributed discrete-time algorithms, the Lyapunov theory and martingale convergence theorem, resilient vector consensus is shown to be reached for all three models when the underlying network satisfies certain stochastic robustness conditions. [ABSTRACT FROM AUTHOR]

Security in wireless sensor network (WSN) is an important approach in the present context as data breaching is becoming more. The data to be routed from source to destination needs more security as WSN has no specific security approach by default. This paper proposes trust based security in WSN using approach. The secure line is drawn from head node to its cluster end point called as angle to provide the security to the nodes which are transferring the data to the head node. Secure line becomes the trust worth line where mobile agent migrates to all the corresponding nodes which are along or near to the secure lines, collects the data and encrypt them. Finally, the data is sent to sink node from head node using a secure path. The agent paradigm is responsible for creating the angle from head node to cluster boundary. Multiple angles can be created if numbers of nodes are more and deployed at different locations. The result shows that the security provided is much better to combat the intruder involvement to breach data along with better network lifetime and minimum delay than compare to conventional techniques. [ABSTRACT FROM AUTHOR]

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.

A mobile agent navigating along edges of a simple connected unweighted graph, either finite or countably infinite, has to find an inert target (treasure) hidden in one of the nodes. This task is known as treasure hunt. The agent has no a priori knowledge of the graph, of the location of the treasure, or of the initial distance to it. The cost of a treasure hunt algorithm is the worst-case number of edge traversals performed by the agent until finding the treasure. Awerbuch et al. [3] considered graph exploration and treasure hunt for finite graphs in a restricted model where the agent has a fuel tank that can be replenished only at the starting node s. The size of the tank is B = 2(1 + a)r, for some positive real constant a, where r, called the radius of the graph, is the maximum distance from s to any other node. The tank of size B allows the agent to make at most -B° edge traversals between two consecutive visits at node s. Let e (d) be the number of edges whose at least one endpoint is at distance less than d from s. Awerbuch et al. [3] conjectured that it is impossible to find a treasure hidden in a node at distance at most d at cost nearly linear in e (d). We first design a deterministic treasure hunt algorithm working in the model without any restrictions on the moves of the agent at cost O(e (d) logd) and then show how to modify this algorithm to work in the model from Awerbuch et al. [3] with the same complexity. Thus, we refute the preceding 20-year-old conjecture. We observe that no treasure hunt algorithm can beat cost T(e (d)) for all graphs, and thus our algorithms are also almost optimal. [ABSTRACT FROM AUTHOR]

A routing model about mobile agent in sensor networks was drawn out, and an optimization problem of mobile agent static route was derived. In order to optimize the route of mobile agent, a target location algorithm in wireless sensor networks was proposed. All the sensor nodes which know target compete to get the mobile agent in order to track the location of targets. Competition rules are defined by the remaining value of the energy and the distance between the nodes and the target. Simulation results showed that this algorithm could provide less energy consumption compared to other schemes and prolong survival cycle time. It balances the network energy, reduces the amount of data transmission in the network, reduces the network energy overhead, prolongs the lifetime of the entire network, and effectively reduces the network delay. [ABSTRACT FROM AUTHOR]

Because of the high infectivity of COVID-19, it is essential to detect the close contacts of patients as soon as possible to contain the outbreak of the epidemic. However, due to the level of technological development, the current methods and research on contact detection require manual participation. This paper proposes a future oriented automation method, which uses mobile agents loaded on sensing devices and edge coordinators to form a multi-agent system on the street. Based on perception, tracking and edge-computing, the contact probability between infected people and pedestrians is estimated. A series of simulations provide the comparison of parameters in application deployment. The simulation results show that the proposed street expropriation mode and edge-computing algorithm can further improve the detection rate. [ABSTRACT FROM AUTHOR]

A team of mobile agents with different labels, starting from different nodes of an unknown anonymous network, must meet at the same node and declare that they all met. This task of gathering was traditionally considered assuming that agents at the same node can exchange information. We ask if this ability of talking is needed. The answer turns out to be no. We design two deterministic algorithms that accomplish gathering in a much weaker model. We only assume that each agent knows how many agents are at the node that it currently occupies. Our first algorithm assumes that agents know some upper bound N on the size of the network, and works in time polynomial in N and in the length l of the smallest label. Our second algorithm does not assume any knowledge about the network, but its complexity is at least exponential in the size of the network and in the labels of agents. Its purpose is to show feasibility of gathering under this harsher scenario. As a by-product we solve, in the same weak model, the fundamental problem of leader election among agents. As an application we solve the gossiping problem in this model: if each agent has a message, all agents can learn all messages. This is perhaps our most surprising finding: agents without any transmitting devices can solve the most general information exchange problem if they can count the number of agents present at visited nodes. [ABSTRACT FROM AUTHOR]

This paper proposes a new forwarding design of inverse optimal formation control laws for mobile agents with limited sensing ranges and driven by both deterministic and stochastic disturbances (drifts, diffusions, and jumps). The disturbances are allowed to be functions of arbitrarily high order polynomial of agent velocities. The proposed control laws guarantee that there is no collision between any agents, and a cost functional penalising both states and controls without having to solve a Hamilton-Jacobi-Bellman equation or a Hamilton-Jacobi-Isaacs equation. The control design is based on the flexibility of the forwarding method. Simulations are also included to illustrate the effectiveness of the proposed control design. [ABSTRACT FROM AUTHOR]

Exploration of an unknown network by one or multiple mobile entities is a well studied problem which has various applications like treasure hunt, collecting data from some node in the network or samples from contaminated mines. In this paper, we study the problem of edge exploration of an n node graph by a mobile agent. The nodes of the graph are anonymous, and the edges at a node of degree d are arbitrarily assigned unique port numbers in the range 0 , 1 , ⋯ , d - 1 . A mobile agent, starting from a node, has to visit all the edges of the graph and stop. The time of the exploration is the number of edges the agent traverses before it stops. The task of exploration can not be performed even for a class of cycles if no additional help is provided. We consider two different ways of providing additional help to the agent by an Oracle. In the first scenario, the nodes of the graph are provided some short labels by the Oracle. In the second scenario, some additional information, called advice, is provided to the agent in the form of a binary string. For the first scenario, we show that exploration can be done by providing constant size labels to the nodes of the graph. For the second scenario, we show that exploration can not be completed within time o (n 8 3) regardless of the advice provided to the agent. We propose an upper bound result by designing an O (n 3) algorithm with O (n log n) advice. We also show a lower bound Ω (n 8 3) on the size of advice to perform exploration in O (n 3) time. In addition, we have done experimental studies on randomly created anonymous graph to analyze time complexity of exploration with O (n log n) size advice. [ABSTRACT FROM AUTHOR]

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]

Consider a group of autonomous mobile computational entities, called agents, arbitrarily placed at some nodes of a dynamic but always connected ring. The agents neither have any knowledge about the size of the ring nor have a common notion of orientation. We consider the Exploration problem where the agents have to collaboratively explore the graph and terminate, with the requirement that each node has to be visited by at least one agent. It has been shown by Luna et al. (2020) [22] that the problem is solvable by two anonymous agents if there is a single observably different node in the ring called landmark node. The problem is unsolvable by any number of anonymous agents in absence of a landmark node. We consider the problem with non-anonymous agents (agents with distinct identifiers) in a ring with no landmark node. The assumption of agents with distinct identifiers is strictly weaker than having a landmark node as the problem is unsolvable by two agents with distinct identifiers in absence of a landmark node. This setting has been recently studied by Mandal et al. (2020) [6]. There it is shown that the problem is solvable in this setting by three agents assuming that they have edge crossing detection capability. Edge crossing detection capability is a strong assumption which enables two agents moving in opposite directions through an edge in the same round to detect each other and also exchange information. In this paper we give an algorithm that solves the problem with three agents without the edge crossing detection capability. • Exploration of a dynamic but always connected ring by autonomous agents is studied. • A deterministic protocol is given that solves the problem with explicit termination. • The agents have unique identifiers, but do not have chirality or edge crossing detection capability. • The algorithm solves the problem with optimum number of agents. • A new problem called Contiguous Agreement is introduced and solved. [ABSTRACT FROM AUTHOR]

Mobile Agent has many benefits over traditional distributed systems such as reducing latency, bandwidth, and costs. Mobile Agent Systems are not fully utilized due to security problems. This paper focuses on mobile agent protection against malicious hosts. A new security mechanism called Checkpoints has been proposed. Checkpoint Mechanism (CPM) aims to protect Mobile Agent against malicious hosts in case of Capturing and Integrity attacks. CPM assumes using a free-roaming mobility mechanism by Mobile agent systems. The main idea behind CPM is to generate multiple versions of Mobile Agent. The multiple version is used to recover Mobile Agent from Capturing and Integrity attacks by untrusted hosts.MA versions are kept in Recovery Host(RH). RH plays a key role in CPM by controlling and monitoring MAs' recovery processes. A prototype method has been used to prove the feasibility of CPM. The p https://dsr.kau.edu.sa/Default-305-ARrototype was implemented by using the .Net framework and C#. full discussion for several scenarios has been done to analyze the feasibility and performance for CPM. As found from this research, CPM has a strong ability to protect Mobile Agents from Capturing and Integrity attacks completely. In addition, there is no negative impact on the overall performance of the mobile agent system. [ABSTRACT FROM AUTHOR]

Quality of service (QoS) is essential for carrying out data transmission using resource-constrained sensor nodes in wireless sensor network (WSN). The introduction of mobile agent-based data aggregation is reported to offer energy efficiency; however, it has limitations, especially using a single mobile agent, where QoS optimization is not feasible. A review of existing studies showcases some dedicated attempts to use a mobile agent-based approach and address QoS enhancements. However, they were never combined studied. Therefore, this paper introduces a unique concept of retaining maximum QoS performance during data aggregation using a single mobile agent. The model introduces a unique communication framework, transmission provisioning using exceptional routine management, and simplified energy modeling. The proposed model has aimed for a lower delay and faster data aggregation speed with lower consumption of transmittance energy. The implementation and assessment of the model are carried out considering the challenging environment of WSN with multiple scales of data priority. The proposed model also contributes to evolving out with simplified communication vectors in a highly decentralized method. MATLAB's simulation outcome shows that the proposed system offers better delay performance, optimal energy management, and faster response time than existing schemes. [ABSTRACT FROM AUTHOR]

Treasure hunt is finding a hidden inert target by a mobile agent. We consider deterministic algorithms for treasure hunt in trees. Our goal is to establish the impact of different kinds of initial knowledge given to the agent on the cost of treasure hunt, defined as the total number of edge traversals until the agent reaches the treasure. The agent can be initially given either a complete map of the tree rooted at its starting node, with all port numbers marked, or a blind map of the tree rooted at its starting node but without port numbers. It may also be given, or not, the distance from the root to the treasure. This yields four different knowledge types that are partially ordered by their precision. The penalty of a less precise knowledge type 풯2 over a more precise knowledge type 풯1 measures intuitively the worst‐case ratio of the cost of an algorithm supplied with knowledge of type 풯2 over the cost of an algorithm supplied with knowledge of type 풯1. Our main results establish penalties for comparable knowledge types in this partial order. For knowledge types with known distance, the penalty for having a blind map over a complete map turns out to be very large. By contrast, for unknown distance, the penalty of having a blind map over having a complete map is small. When a map is provided (either complete or blind), the penalty of not knowing the distance over knowing it is medium. [ABSTRACT FROM AUTHOR]

• We study the problem of pebble-guided treasure hunt by a mobile agent in anonymous graphs. • The mobile agent, starting from a node, must find a treasure located on an unknown node at a distance D. • The time of treasure hunt is defined as the number of edges the agent visits before it finds the treasure. • We propose an algorithm that solves treasure hunt in time O (D log ⁡ Δ) using O (D log ⁡ Δ) pebbles. • We prove a lower bound of Ω (D log ⁡ Δ) on time of treasure hunt regardless of the number of pebbles used. We study the problem of treasure hunt in a graph by a mobile agent. The nodes in the graph are anonymous and the edges at any node v of degree d e g (v) are labeled arbitrarily as 0 , 1 , ... , d e g (v) − 1. A mobile agent, starting from a node, must find a stationary object, called treasure that is located on an unknown node at a distance D from its initial position. The agent finds the treasure when it reaches the node where the treasure is present. The time of treasure hunt is defined as the number of edges the agent visits before it finds the treasure. The agent does not have any prior knowledge about the graph or the position of the treasure. An Oracle, that knows the graph, the initial position of the agent, and the position of the treasure, places some pebbles on the nodes, at most one per node, of the graph to guide the agent towards the treasure. We target to answer the question: what is the fastest possible treasure hunt algorithm regardless of the number of pebbles are placed? We show an algorithm that uses O (D log ⁡ Δ) pebbles to find the treasure in a graph G in time O (D log ⁡ Δ) , where Δ is the maximum degree of a node in G and D is the distance from the initial position of the agent to the treasure. We show a matching lower bound of Ω (D log ⁡ Δ) on time of the treasure hunt using any number of pebbles. [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]

Gathering is a key task in distributed and mobile systems, which becomes significantly harder if some agents are subject to Byzantine faults, known as being the worst ones. We propose here to study the task of Byzantine gathering in an arbitrary graph: despite the presence of Byzantine agents, the goal is to ensure that all the other (good) agents, executing the same algorithm, eventually meet at the same node and stop. Initially, each agent gets as input a different label and some global knowledge that is common to all agents. The agents move in synchronous rounds and communicate with each other only when located at the same node. There are f Byzantine agents. These agents act in an unpredictable way, e.g., they may convey arbitrary informations or forge any label. In the literature, the gathering algorithms working in such a context all have an exponential time complexity in the number n of nodes and the labels of the good agents. In this paper, we design a deterministic algorithm to solve Byzantine gathering in time polynomial in n and the logarithm ℓ of the smallest label of a good agent, provided the agents are a strong team i.e., a team where the number of good agents is at least some quadratic polynomial in f. Our algorithm requires global knowledge that can be coded in O (log log log n) bits: we prove this size is of optimal order of magnitude to obtain a polynomial time complexity in n and ℓ with strong teams. [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]

In the path planning using Q-learning of the mobile agent, the convergence speed is too slow. So, based on Q-learning, two hybrid algorithms are proposed to improve the above problem in this paper. One algorithm is combining Manhattan distance and Q-learning (CMD-QL); the other one is combining flower pollination algorithm and Q-learning (CFPA-QL). In the former algorithm, the Q table is firstly initialized with Manhattan distance to enhance the learning efficiency of the initial stage of Q-learning; secondly, the selection strategy of the ε-greedy action is improved to balance the exploration-exploitation relationship of the mobile agent's actions. In the latter algorithm, the flower pollination algorithm is first used to initialize the Q table, so that Q-learning can obtain the necessary prior information which can improve the overall learning efficiency; secondly, the ε-greedy strategy under the minimum value of the exploration factor is adopted, which makes effective use of the action with high value. Both algorithms have been tested under known, partially known, and unknown environments, respectively. The test results show that the CMD-QL and CFPA-QL algorithms proposed in this paper can converge to the optimal path faster than the single Q-learning method, besides the CFPA-QL algorithm has the better efficiency. [ABSTRACT FROM AUTHOR]