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The collection of sensory data is crucial for cyber-physical systems. Employing mobile agents (MAs) to collect data from sensors offers a new dimension to reduce and balance their energy consumption but leads to large data collection latency due to MAs’ limited velocity. Most existing research effort focuses on the offline mobile data collection (MDC), where the MAs collect data from sensors based on preoptimized tours. However, the efficiency of these offline MDC solutions degrades when the data generation of sensors varies. In this paper, we investigate the on-demand MDC; that is, MAs collect data based on the real-time data collection requests from sensors. Specifically, we construct queuing models to describe the First-Come-First-Serve-based MDC with a single MA and multiple MAs, respectively, laying a theoretical foundation. We also use three examples to show how such analysis guides online MDC in practice. [ABSTRACT FROM AUTHOR]

In this paper, a mobile agent based distributed EM (Expectation Maximization) algorithm is developed for density estimation and data clustering in sensor networks. It has been assumed that sensor measurements can be statistically modeled by a common Gaussian mixture model. This algorithm not only executes the EM algorithm in a distributed manner, but reduces the number of iterations of the EM algorithm and increases its convergence rate. Convergence of the proposed method will also be studied analytically and will be shown that the estimated parameters will eventually converge to their true values. Finally, the proposed method will be applied to synthetic data sets in order to show its promising performance. [ABSTRACT FROM AUTHOR]

Recent developments in extremum seeking theory have established a general framework for the methodology, although the specific implementations, particularly in the context of multi-agent systems, have not been demonstrated. In this work, a group of sensor-enabled vehicles is used in the context of the extremum seeking problem using both local and global optimisation algorithms to locate the extremum of an unknown scalar field distribution. For the former, the extremum seeker exploits estimates of gradients of the field from local dithering sensor measurements collected by the mobile agents. It is assumed that a distributed coordination which ensures uniform asymptotic stability with respect to a prescribed formation of the agents is employed. An inherent advantage of the frameworks is that a broad range of nonlinear programming algorithms can be combined with a wide class of cooperative control laws to perform extreme source seeking. Semi-global practical asymptotically stable convergence to local extrema is established in the presence of field sampling noise. Subsequently, global extremum seeking with multiple agents is investigated and shown to give rise to robust practical convergence whose speed can be improved via computational parallelism. Nonconvex field distributions with local extrema can be accommodated within this global framework. [ABSTRACT FROM AUTHOR]

Wireless sensor networks are increasingly adopted both in aircraft and civil structural health monitoring. However, due to the limited resources on a wireless sensor node, structural evaluation ability of the wireless sensor network is also limited, especially for large-scale structures. This paper presents a multi-agent cooperation system based on mobile agent technology for wireless sensor network-based structural health monitoring which deals with the evaluation of large-scale structure. Mobile agent with the signal processing or evaluation algorithm is designed to migrate among different sensor nodes and perform network self-organization, data processing, information fusion, and damage estimation. This method can reduce the request to the sensor nodes and achieve a better monitoring and evaluation performance through multiagent cooperation. The proposed mobile multiagent system is evaluated by a large dimension aerospace aluminum structure monitoring experiment in which strain distribution and joint failure are monitored by different sensors. Experimental results show that the system can significantly improve the monitoring performance for large-scale structures. [ABSTRACT FROM AUTHOR]

We consider the coalescence or gathering problem: a set of k mobile agents (robots) with distinct identifiers have to locate one another and gather at a common location. Agents may face several challenges: swarms of agent may be too large to simultaneously observe one another, agent sensors may be subject to noise, and some agents may be malicious. For small swarms, we design an algorithm coalescing all trustworthy agents despite sensor noise and an arbitrary number of malicious agents. This algorithm requires that all coalescing agents be able to simultaneously observe a single agent, limiting its practical scalability. For arbitrarily large swarms we design an algorithm achieving coalescence as long as the number of malicious agents near any given trustworthy agent is bounded. In both cases, our algorithms work by reduction to blackbox solutions to well-studied problems, allowing them to be used in any environment and for any type of agents for which deterministic rendezvous, agent state estimation, and pair-wise cohesion algorithms are available. [ABSTRACT FROM AUTHOR]

Abstract: Multiple sensing agent system is generally used to represent practical distributed multiple sensor systems at an abstract level without worrying about the particulars of sensors, where agents represent the autonomous sensors. There are many multiagent coordination models which require relatively high memory and computation capacities of agents; thus those models are impractical for multiple sensing agent systems where agents have very limited memories and capacities. To fully relax agents from observing and memorizing other agents’ actions, this paper proposes the concept of tag vector in multiagent coordination and proposes a novel tag-based solution for data sensing conflicts in multiple sensing agent systems; in the presented tag-based solution, agents can coordinate their sensed data according to their tags. The theoretical proofs and case study prove that the proposed tag-based solution can effectively solve the data sensing conflicts by making the sensed data more consistent and reducing the coordination expense. [Copyright &y& Elsevier]

Abstract: This paper performs coverage analysis of mobile agent trajectory utilizing discrete event system models and employing state-based notions of opacity. Non-deterministic finite automata with partial observation on their transitions are used to simultaneously capture both the kinematic model of a mobile agent and the information that becomes available by a set of sensors that are deployed in a given environment. The information provided by the set of sensors is analyzed to track the passage of a mobile agent through certain secret (strategic) locations at specific time instants using state-space notions of opacity, which arise naturally as the way to capture/analyze secrecy and privacy considerations in such settings, and to answer related coverage questions. Realistic examples of two-dimensional environments equipped with sensors monitoring the location of a mobile agent that follows a known kinematic model are subsequently analyzed by adopting existing tools in the discrete event systems area. [Copyright &y& Elsevier]

We present a novel system that recognizes and records the motional activities of a person using a mobile phone. Wireless sensors measuring the intensity of motions are attached to body parts of the user. Sensory data is collected by a mobile application that recognizes prelearnt activities in real-time. For efficient motion pattern recognition of gestures and postures, feed-forward backpropagation neural networks are adopted. The design and implementation of the system are presented along with the records of our experiences. Results show high recognition rates for distinguishing among six different motion patterns. The recognized activity can be used as an additional retrieval key in an extensive mobile memory recording and sharing project. Power consumption measurements of the wireless communication and the recognition algorithm are provided to characterize the resource requirements of the system. [ABSTRACT FROM AUTHOR]

In open heterogeneous context-aware pervasive computing systems, suitable context models and reasoning approaches are necessary to enable collaboration and distributed reasoning among agents. This paper proposes, develops, and demonstrates the following: 1) a novel context model and reasoning approach developed with concepts from the state-space model, which describes context and situations as geometrical structures in a multidimensional space; and 2) a context algebra based on the model, which enables distributed reasoning by merging and partitioning context models that represent different perspectives of computing entities over the object of reasoning. We show how merging and reconciling different points of view over context enhances the out- comes of reasoning about the context. We develop and evaluate our proposed algebraic operators and reasoning approaches with cases using real sensors and with simulations. We embed agents and mobile agents with these modeling and reasoning capabilities, thus facilitating context-aware and adaptive mobile agents operating in open pervasive environments. [ABSTRACT FROM AUTHOR]

A wireless sensor network designed according to the sensor network with mobile agents (SENMA) architecture is engaged in a detection task, with a mobile agent (MA) that sequentially queries the network's nodes. The focus is on the effect of censoring: sensors respond to the query from the MA only if the local observations are deemed sufficiently informative; otherwise, they stay silent. Delivered data, if any, can be either unquantized or quantized to a single bit. The study is limited to shift-in-mean problems, involving two simple statistical hypotheses, where the noise distribution must be an even function but is otherwise arbitrary. Simple analytical relationships characterizing the tradeoff between the detection delay and the energy consumption of the network are derived, and examples of their applications are provided. [ABSTRACT FROM AUTHOR]

The wireless sensor network is an emerging technology that may greatly aid humans by providing ubiquitous sensing, computing and communication capabilities, through which people can more closely interact with the environment wherever they go. To be context-aware, one of the central issues in sensor networks is location tracking, whose goal is to monitor the roaming path of a moving object. While similar to the location-update problem in PCS networks, this problem is more challenging in two senses: (1) there is neither a central control mechanism nor a backbone network in such an environment and (2) the wireless communication bandwidth is very limited. In this paper, we propose a novel protocol based on the mobile agent paradigm. Once a new object is detected, a mobile agent will be initiated to track the roaming path of the object. The agent is mobile since it will choose the sensor closest to the object to stay. The agent may invite some nearby slave sensors to cooperatively position the object and inhibit other irrelevant (i.e. farther) sensors from tracking the object. As a result, the communication and sensing overheads are greatly reduced. Our prototyping of the location-tracking mobile agent based on IEEE 802.11b NICs and our experimental experiences are also reported. [ABSTRACT FROM AUTHOR]

Describes the deployment of mobile agent in Distributed Sensor Networks (DSN). System under the mobile-agent-based paradigm; Application of the agent to integrate pre-processed data located at local sensor nodes; Use of target classification as an example to illustrate how mobile-agent-based DSN supports high performance distributed integration.

Mobile agent is a kind of program which can transfer via asynchronous mode independently in the sensor network with outstanding prospects in application. However, due to the openness of the sensor network, mobile agents are facing the threat of security, such as being stolen and modified. How to protect sensors from attacks of malicious mobile agents becomes an important issue in the field. Traditional access control strategies such as hybrid encryption mechanism, partial results of the package, and other methods have some defects in the application. We design a multisensor interaction trust model with complete β distribution and introduce incomplete β distribution to optimize the trust model according to the actual situation of detection data loss for mobile agent system in the wireless sensor networks. In addition, the introduction of the malicious behavior feedback mechanism ensures the security of sensors in the mobile agent system. The experimental results show that the reputation model of incomplete β distribution can simulate the actual situation well, resist the attacks of malicious agents, and ensure the security of sensors in the system. [ABSTRACT FROM AUTHOR]

The development of agent technologies for sensor networks has received increasing research attention within both the sensor network and multi-agent systems research communities. The International Workshops on Agent Technologies for Sensor Networks (ATSN) held in 2007, 2008 and 2009 sought to bring these communities together, and this special issue of The Computer Journal presents extended versions of some of the papers that appeared at these workshops, along with new submissions specifically for this journal. [ABSTRACT FROM AUTHOR]

This paper considers the problem of localizing multiple agents, e.g. unmanned aerial vehicles (UAVs), robots, etc., moving in two-dimensional space when the known data comprise 1) the inter-agent distances, and 2) the angle subtended at each agent by lines drawn from two landmarks at known positions. Later it is shown that this result has direct application in a different general robotic problem, viz. robot-to-robot relative pose determination (relative reference frame determination), using measured distances. The methods proposed are validated through simulations and experiments. [ABSTRACT FROM PUBLISHER]