1,420 research outputs found
Amorphous Placement and Informed Diffusion for Timely Monitoring by Autonomous, Resource-Constrained, Mobile Sensors
Personal communication devices are increasingly equipped with sensors for passive monitoring of encounters and surroundings. We envision the emergence of services that enable a community of mobile users carrying such resource-limited devices to query such information at remote locations in the ïŹeld in which they collectively roam. One approach to implement such a service is directed placement and retrieval (DPR), whereby readings/queries about a specific location are routed to a node responsible for that location. In a mobile, potentially sparse setting, where end-to-end paths are unavailable, DPR is not an attractive solution as it would require the use of delay-tolerant (flooding-based store-carry-forward) routing of both readings and queries, which is inappropriate for applications with data freshness constraints, and which is incompatible with stringent device power/memory constraints. Alternatively, we propose the use of amorphous placement and retrieval (APR), in which routing and ïŹeld monitoring are integrated through the use of a cache management scheme coupled with an informed exchange of cached samples to diffuse sensory data throughout the network, in such a way that a query answer is likely to be found close to the query origin. We argue that knowledge of the distribution of query targets could be used effectively by an informed cache management policy to maximize the utility of collective storage of all devices. Using a simple analytical model, we show that the use of informed cache management is particularly important when the mobility model results in a non-uniform distribution of users over the ïŹeld. We present results from extensive simulations which show that in sparsely-connected networks, APR is more cost-effective than DPR, that it provides extra resilience to node failure and packet losses, and that its use of informed cache management yields superior performance
Lifetime Maximization of Wireless Sensor Networks with a Mobile Source Node
We study the problem of routing in sensor networks where the goal is to
maximize the network's lifetime. Previous work has considered this problem for
fixed-topology networks. Here, we add mobility to the source node, which
requires a new definition of the network lifetime. In particular, we redefine
lifetime to be the time until the source node depletes its energy. When the
mobile node's trajectory is unknown in advance, we formulate three versions of
an optimal control problem aiming at this lifetime maximization. We show that
in all cases, the solution can be reduced to a sequence of Non- Linear
Programming (NLP) problems solved on line as the source node trajectory
evolves.Comment: A shorter version of this work will be published in Proceedings of
2016 IEEE Conference on Decision and Contro
Wearable and Implantable Wireless Sensor Network Solutions for Healthcare Monitoring
Wireless sensor network (WSN) technologies are considered one of the key research areas in computer science and the healthcare application industries for improving the quality of life. The purpose of this paper is to provide a snapshot of current developments and future direction of research on wearable and implantable body area network systems for continuous monitoring of patients. This paper explains the important role of body sensor networks in medicine to minimize the need for caregivers and help the chronically ill and elderly people live an independent life, besides providing people with quality care. The paper provides several examples of state of the art technology together with the design considerations like unobtrusiveness, scalability, energy efficiency, security and also provides a comprehensive analysis of the various benefits and drawbacks of these systems. Although offering significant benefits, the field of wearable and implantable body sensor networks still faces major challenges and open research problems which are investigated and covered, along with some proposed solutions, in this paper
Self-healing in unattended wireless sensor networks
Wireless sensor networks (WSNs) appeal to a wide range of applications that involve the monitoring of various physical phenomena. However, WSNs are subject to many threats. In particular, lack of pervasive tamper-resistant hardware results in sensors being easy targets for compromise. Having compromised a sensor, the adversary learns all the sensor secrets, allowing it to later encrypt/decrypt or authenticate messages on behalf of that sensor. This threat is particularly relevant in the novel unattended wireless sensor networks (UWSNs) scenario. UWSNs operate without constant supervision by a trusted sink. UWSN?s unattended nature and increased exposure to attacks prompts the need for special techniques geared towards regaining security after being compromised. In this article, we investigate cooperative self-healing in UWSNs and propose various techniques to allow unattended sensors to recover security after compromise. Our techniques provide seamless healing rates even against a very agile and powerful adversary. The effectiveness and viability of our proposed techniques are assessed by thorough analysis and supported by simulation results. Finally, we introduce some real-world issues affecting UWSN deployment and provide some solutions for them as well as a few open problems calling for further investigation
GossiCrypt: Wireless Sensor Network Data Confidentiality Against Parasitic Adversaries
Resource and cost constraints remain a challenge for wireless sensor network
security. In this paper, we propose a new approach to protect confidentiality
against a parasitic adversary, which seeks to exploit sensor networks by
obtaining measurements in an unauthorized way. Our low-complexity solution,
GossiCrypt, leverages on the large scale of sensor networks to protect
confidentiality efficiently and effectively. GossiCrypt protects data by
symmetric key encryption at their source nodes and re-encryption at a randomly
chosen subset of nodes en route to the sink. Furthermore, it employs key
refreshing to mitigate the physical compromise of cryptographic keys. We
validate GossiCrypt analytically and with simulations, showing it protects data
confidentiality with probability almost one. Moreover, compared with a system
that uses public-key data encryption, the energy consumption of GossiCrypt is
one to three orders of magnitude lower
An architecture for distributed ledger-based M2M auditing for Electric Autonomous Vehicles
Electric Autonomous Vehicles (EAVs) promise to be an effective way to solve
transportation issues such as accidents, emissions and congestion, and aim at
establishing the foundation of Machine-to-Machine (M2M) economy. For this to be
possible, the market should be able to offer appropriate charging services
without involving humans. The state-of-the-art mechanisms of charging and
billing do not meet this requirement, and often impose service fees for value
transactions that may also endanger users and their location privacy. This
paper aims at filling this gap and envisions a new charging architecture and a
billing framework for EAV which would enable M2M transactions via the use of
Distributed Ledger Technology (DLT)
Quality-of-service in wireless sensor networks: state-of-the-art and future directions
Wireless sensor networks (WSNs) are one of todayâs most prominent instantiations
of the ubiquituous computing paradigm. In order to achieve high
levels of integration, WSNs need to be conceived considering requirements
beyond the mere systemâs functionality. While Quality-of-Service (QoS) is
traditionally associated with bit/data rate, network throughput, message delay
and bit/packet error rate, we believe that this concept is too strict, in
the sense that these properties alone do not reflect the overall quality-ofservice
provided to the user/application. Other non-functional properties
such as scalability, security or energy sustainability must also be considered
in the system design. This paper identifies the most important non-functional
properties that affect the overall quality of the service provided to the users,
outlining their relevance, state-of-the-art and future research directions
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