2,335 research outputs found
Collaborative signal and information processing for target detection with heterogeneous sensor networks
In this paper, an approach for target detection and acquisition with heterogeneous sensor networks through strategic resource allocation and coordination is presented. Based on sensor management and collaborative signal and information processing, low-capacity low-cost sensors are strategically deployed to guide and cue scarce high performance sensors in the network to improve the data quality, with which the mission is eventually completed more efficiently with lower cost. We focus on the problem of designing such a network system in which issues of resource selection and allocation, system behaviour and capacity, target behaviour and patterns, the environment, and multiple constraints such as the cost must be addressed simultaneously. Simulation results offer significant insight into sensor selection and network operation, and demonstrate the great benefits introduced by guided search in an application of hunting down and capturing hostile vehicles on the battlefield
Reliability of Mobile Agents for Reliable Service Discovery Protocol in MANET
Recently mobile agents are used to discover services in mobile ad-hoc network
(MANET) where agents travel through the network, collecting and sometimes
spreading the dynamically changing service information. But it is important to
investigate how reliable the agents are for this application as the
dependability issues(reliability and availability) of MANET are highly affected
by its dynamic nature.The complexity of underlying MANET makes it hard to
obtain the route reliability of the mobile agent systems (MAS); instead we
estimate it using Monte Carlo simulation. Thus an algorithm for estimating the
task route reliability of MAS (deployed for discovering services) is proposed,
that takes into account the effect of node mobility in MANET. That mobility
pattern of the nodes affects the MAS performance is also shown by considering
different mobility models. Multipath propagation effect of radio signal is
considered to decide link existence. Transient link errors are also considered.
Finally we propose a metric to calculate the reliability of service discovery
protocol and see how MAS performance affects the protocol reliability. The
experimental results show the robustness of the proposed algorithm. Here the
optimum value of network bandwidth (needed to support the agents) is calculated
for our application. However the reliability of MAS is highly dependent on link
failure probability
Cognitive Connectivity Resilience in Multi-layer Remotely Deployed Mobile Internet of Things
Enabling the Internet of things in remote areas without traditional
communication infrastructure requires a multi-layer network architecture. The
devices in the overlay network are required to provide coverage to the underlay
devices as well as to remain connected to other overlay devices. The
coordination, planning, and design of such two-layer heterogeneous networks is
an important problem to address. Moreover, the mobility of the nodes and their
vulnerability to adversaries pose new challenges to the connectivity. For
instance, the connectivity of devices can be affected by changes in the
network, e.g., the mobility of the underlay devices or the unavailability of
overlay devices due to failure or adversarial attacks. To this end, this work
proposes a feedback based adaptive, self-configurable, and resilient framework
for the overlay network that cognitively adapts to the changes in the network
to provide reliable connectivity between spatially dispersed smart devices. Our
results show that if sufficient overlay devices are available, the framework
leads to a connected configuration that ensures a high coverage of the mobile
underlay network. Moreover, the framework can actively reconfigure itself in
the event of varying levels of device failure.Comment: To appear in IEEE Global Communications Conference (Globecom 2017
Agent-based Sensor-Mission Assignment for Tasks Sharing Assets
(c) IFAAMASPeer reviewedPostprin
Performance evaluation of two-fuzzy based cluster head selection systems for wireless sensor networks
Sensor networks supported by recent technological advances in low power wireless communications along with silicon integration of various functionalities are emerging as a critically important computer class that enable novel and low cost applications. There are many fundamental problems that sensor networks research will have to address in order to ensure
a reasonable degree of cost and system quality. Cluster formation and cluster head selection are important problems in sensor
network applications and can drastically affect the network’s communication energy dissipation. However, selecting of the
cluster head is not easy in different environments which may have different characteristics. In this paper, in order to deal with this problem, we propose two fuzzy-based systems for cluster head selection in sensor networks. We call these systems: FCHS
System1 and FCHS System2. We evaluate the proposed systems by simulations and have shown that FCHS System2 make a good selection of the cluster head compared with FCHS System1 and another previous system.Peer ReviewedPostprint (published version
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