In wireless sensor-actor networks, sensors probe their surroundings and forward their data to actor nodes. Actors collaboratively respond to achieve predefined application mission. Since actors have to coordinate their operation, it is necessary to maintain a strongly connected network topology at all times. Moreover, the length of the inter-actor communication paths may be constrained to meet latency requirements. However, a failure of an actor may cause the network to partition into disjoint blocks and would, thus, violate such a connectivity goal. One of the effective recovery methodologies is to autonomously reposition a subset of the actor nodes to restore connectivity. Contemporary recovery schemes either impose high node relocation overhead or extend some of the inter-actor data paths. This paper overcomes these shortcomings and presents a Least-Disruptive topology Repair (LeDiR) algorithm. LeDiR relies on the local view of a node about the network to devise a recovery plan that relocates the least number of nodes and ensures that no path between any pair of nodes is extended. LeDiR is a localized and distributed algorithm that leverages existing route discovery activities in the network and imposes no additional prefailure communication overhead. The performance of LeDiR is analyzed mathematically and validated via extensive simulation experiments.

In Wireless Sensor-Actor Networks (WSANs), sensors probe their surroundings and send their data to more capable actor nodes. The actors' response requires them to coordinate their operation. Therefore, a strongly connected inter-actor topology is necessary and tolerance of an actor failure becomes a design requirement. Autonomous repositioning of actors has been deemed as an effective recovery strategy. In this paper, we present a distributed network recovery scheme called Least-Movement Topology Repair (LeMoToR). To restore connectivity, LeMoToR relies on the local view of a node about the network and strives to relocate the least number of nodes. It also reduces the total travelled distance and overall inter-node communication complexity. LeMoToR do not imposes pre-failure communication overhead and utilises existing path discovery activities in the network to know the structure of the topology. The performance of LeMoToR is validated analytically and through simulation. The validation results demonstrate the effectiveness of LeMoToR.

This article surveys immersive communication environments and focuses on high-level issues and applications. The authors classify the immersive computing environments into three major categories: entertainment, business and society, and simulated learning and education.

In Wireless Sensor-Actor Networks (WSANs), sensors probe their surroundings and send their data to more capable actor nodes in order to execute an application task. The actors' response is mostly collaborative and requires them to coordinate their operation. Therefore, a strongly connected inter-actor topology would be necessary at all time and tolerance of an actor failure becomes a design requirement. Autonomous repositioning of actor nodes has been deemed as an effective recovery strategy. This paper presents a Least-Movement Topology Repair (LeMoToR) algorithm. LeMoToR is a distributed scheme that relies on the local view of a node about the network. To restore connectivity, LeMoToR strives to relocate the least number of nodes and reduce the traveled distance and message complexity. Unlike contemporary schemes that maintain 1 or 2-hop neighbor lists, LeMoToR utilizes existing path discovery activities in the network in order to know the structure of the topology and avoids imposing additional pre-failure communication overhead. The simulation results validate the effectiveness of LeMoToR.

In Wireless Sensor-Actor Networks (WSANs), actors collect sensor readings and respond collaboratively to achieve an application mission. Since actors coordinate their operation, a strongly connected network topology would be required at all time. In addition, the path between actors may have to be capped in order to meet latency constraints. However, a failure of an actor may cause the network to partition into disjoint blocks and would thus violate such connectivity goal. One of the effective recovery methodologies is to autonomously reposition a subset of the actor nodes to restore connectivity. Contemporary schemes rely on maintaining 1 or 2-hop neighbor lists and predetermine criteria for node's involvement in the recovery. However, 1-hop based schemes often impose high node relocation overhead. In addition, the repaired inter-actor topology using 2-hop schemes often differs significantly from its pre-failure status and some inter-actor data paths may get extended. This paper presents a Least-Disruptive topology Repair (LeDiR) algorithm. LeDiR relies on the local view of a node about the network in order to devise a recovery plan that relocates the least number of nodes and ensures that no path between any pair of nodes is extended. LeDiR is a localized and distributed algorithm that leverages existing path discovery activities and imposes no additional pre-failure communication overhead. LeDiR is validated through simulation and is shown to outperform existing schemes.

Recent years have witnessed a growing interest in the applications of wireless sensor networks (WSNs). In some of these applications, such as search and rescue and battlefield reconnaissance, a set of mobile nodes is deployed in order to collectively survey an area of interest and/or perform specific surveillance tasks. Such collaboration among the sensors requires internode interaction and thus maintaining network connectivity is critical to the effectiveness of WSNs. While connectivity can be provisioned at startup time and then sustained through careful coordination when nodes move, a sudden failure of a node poses a challenge since the network may get partitioned. This paper presents RIM; a distributed algorithm for Recovery through Inward Motion. RIM strives to efficiently restore the network connectivity after a node failure. Instead of performing a networkwide analysis to assess the impact of the node failure and orchestrate a course of action, RIM triggers a local recovery process by relocating the neighbors of the lost node. In addition to minimizing the messaging overhead, RIM opts to reduce the distance that the individual nodes have to travel during the recovery. The correctness of the RIM algorithm is proven and the incurred overhead is analyzed. The performance of RIM is validated through simulation experiments.

In Wireless Sensor and Actor Networks (WSANs) a connected interactor topology is desirable in order for the deployed actors to work collaboratively. If a critical actor fails causing the inter-actor network to get partitioned into disjoint segments, the other actors close to the faulty node often exploit their mobility to autonomously restore the lost inter-actor connectivity. However, such a solution focuses on resource efficiency and assumes no constraints on the mobility of actors which can be impractical in the real scenarios. In addition, since actors need to carry out tasks to meet the application level requirements, unconstrained movement of actor(s) to restore interactor connectivity can cause a major failure at the application level. This paper presents C2AM; a recovery algorithm that factors in application level constraints on actor's mobility while restoring the network connectivity. In addition to considering physical level requirements, C2AM accounts for application level concerns as well in order to avoid major disruptions to ongoing missions. Simulation results have validated the effectiveness of the algorithm in maintaining both objectives.

Recent years have witnessed a growing interest in applications of wireless sensor and actor networks (WSANs). In these applications, a set of mobile actor nodes are deployed in addition to sensors in order to collect sensors' data and perform specific tasks in response to detected events/objects. In most scenarios, actors have to respond collectively, which requires interactor coordination. Therefore, maintaining a connected interactor network is critical to the effectiveness of WSANs. However, WSANs often operate unattended in harsh environments where actors can easily fail or get damaged. An actor failure may lead to partitioning the interactor network and thus hinder the fulfillment of the application requirements. In this paper, we present DARA, a distributed actor recovery algorithm, which opts to efficiently restore the connectivity of the interactor network that has been affected by the failure of an actor. Two variants of the algorithm are developed to address 1- and 2-connectivity requirements. The idea is to identify the least set of actors that should be repositioned in order to reestablish a particular level of connectivity. DARA strives to localize the scope of the recovery process and minimize the movement overhead imposed on the involved actors. The effectiveness of DARA is validated through simulation experiments.

The past few years have witnessed increased interest in the potential use of wireless sensor networks (WSNs) in applications such as disaster management, combat field reconnaissance, border protection and security surveillance. Sensors in these applications are expected to be remotely deployed in large numbers and to operate autonomously in unattended environments. To support scalability, nodes are often grouped into disjoint and mostly non-overlapping clusters. In this paper, we present a taxonomy and general classification of published clustering schemes. We survey different clustering algorithms for WSNs; highlighting their objectives, features, complexity, etc. We also compare of these clustering algorithms based on metrics such as convergence rate, cluster stability, cluster overlapping, location-awareness and support for node mobility.

The subject of wireless networks has recently gained a lot of attention from research community to investigate. The well-organized subdivision of a wireless network into coherent, mostly non-overlapping clusters of physically close nodes is a significant building block in the design of well-organized upper layer network functions such as energy saving, routing, stability, coverage and data aggregation. In our paper, we present a snapshot of different clustering techniques for wireless networks. We also present comparative analysis of different clustering mechanisms based on metrics such as load balancing, efficiency of coverage, energyawareness, cluster stability, routing overhead control, dynamic changes of topology and locality.

Wireless Sensor Networks (WSNs) are playing a fundamental role in emerging pervasive platforms that have potential to host a wide range of next generation civil and military applications. Inexpensive sensor nodes are deployed to the sensing area with little mobility and high density. Furthermore, in many scenarios WSNs are of interest to adversaries and they become susceptible to some types of attacks since they are deployed in open and unprotected environments and are constituted of cheap small devices. Since preventive mechanisms provide no surety to hold the intruder, an intrusion detection system (IDS) running beside preventive mechanism will greatly increase the security of network. Introducing IDS in wireless media is not as similar to that of wired systems due to the differences in capturing audit data and availability of resources. This paper proposes a method of implementing the IDS on cluster-based WSNs using multi-hop data communication.