https://www.science.smith.edu/~jcardell/Courses/EGR328/Readings/WSNSurvey2.pdf

Wireless sensor network survey

The term ‘‘Internet-of-Things’’ is used as an umbrella keyword for covering various aspects related to the extension of the Internet and the Web into the physical realm, by means of the widespread deployment of spatially distributed devices with embedded identification, sensing and/or actuation capabilities. Internet-of-Things envisions a future in which digital and physical entities can be linked, by means of appropriate information and communication technologies, to enable a whole new class of applications and services. In this article, we present a survey of technologies, applications and research challenges for Internetof-Things.

/pdf/internet-of-things-vision-applications-and-research-4xfstaiv80.pdf

Internet of things: Vision, applications and research challenges

In the last years, wireless sensor networks (WSNs) have gained increasing attention from both the research community and actual users. As sensor nodes are generally battery-powered devices, the critical aspects to face concern how to reduce the energy consumption of nodes, so that the network lifetime can be extended to reasonable times. In this paper we first break down the energy consumption for the components of a typical sensor node, and discuss the main directions to energy conservation in WSNs. Then, we present a systematic and comprehensive taxonomy of the energy conservation schemes, which are subsequently discussed in depth. Special attention has been devoted to promising solutions which have not yet obtained a wide attention in the literature, such as techniques for energy efficient data acquisition. Finally we conclude the paper with insights for research directions about energy conservation in WSNs.

/pdf/energy-conservation-in-wireless-sensor-networks-a-survey-1bl7d2obnm.pdf

Energy conservation in wireless sensor networks: A survey

https://www.cs.montana.edu/courses/csci566/Ref/WMSN-Survey.pdf

A survey on wireless multimedia sensor networks

Increasingly ubiquitous communication networks and connectivity via portable devices have engendered a host of applications in which sources, for example people and environmental sensors, send updates of their status to interested recipients. These applications desire status updates at the recipients to be as timely as possible; however, this is typically constrained by limited network resources. In this paper, we employ a time-average age metric for the performance evaluation of status update systems. We derive general methods for calculating the age metric that can be applied to a broad class of service systems. We apply these methods to queue-theoretic system abstractions consisting of a source, a service facility and monitors, with the model of the service facility (physical constraints) a given. The queue discipline of first-come-first-served (FCFS) is explored. We show the existence of an optimal rate at which a source must generate its information to keep its status as timely as possible at all its monitors. This rate differs from those that maximize utilization (throughput) or minimize status packet delivery delay. While our abstractions are simpler than their real-world counterparts, the insights obtained, we believe, are a useful starting point in understanding and designing systems that support real time status updates.

/pdf/real-time-status-how-often-should-one-update-3yjrq72m61.pdf

Real-time status: How often should one update?

In wireless sensor networks, energy efficiency is crucial to achieving satisfactory network lifetime. To reduce the energy consumption significantly, a node should turn off its radio most of the time, except when it has to participate in data forwarding. We propose a new technique, called sparse topology and energy management (STEM), which efficiently wakes up nodes from a deep sleep state without the need for an ultra low-power radio. The designer can trade the energy efficiency of this sleep state for the latency associated with waking up the node. In addition, we integrate STEM with approaches that also leverage excess network density. We show that our hybrid wakeup scheme results in energy savings of over two orders of magnitude compared to sensor networks without topology management. Furthermore, the network designer is offered full flexibility in exploiting the energy-latency-density design space by selecting the appropriate parameter settings of our protocol.

/pdf/optimizing-sensor-networks-in-the-energy-latency-density-a2oi5xhc3n.pdf

Optimizing sensor networks in the energy-latency-density design space

In wireless sensor networks, energy efficiency is crucial to achieve satisfactory network lifetime. In order to reduce the energy consumption of a node significantly, its radio needs to be turned off. Yet, some nodes have to participate in multi-hop packet forwarding. We tackle this issue by exploiting two degrees of freedom in topology management: the path setup latency and the network density. First, we propose a new technique called Sparse Topology and Energy Management (STEM), which aggressively puts nodes to sleep. It provides a method to wake up nodes only when they need to forward data, where latency is traded off for energy savings. Second, STEM integrates efficiently with existing approaches that leverage the fact that nearby nodes can be equivalent for traffic forwarding. In this case, an increased network density results in more energy savings. We analyze a hybrid scheme, which takes advantage of both setup latency and network density to increase the nodes' lifetime. Our results show improvements of nearly two orders of magnitude compared to sensor networks without topology management.

/pdf/topology-management-for-sensor-networks-exploiting-latency-1yaiwb2eco.pdf

Topology management for sensor networks: exploiting latency and density

In wireless sensor networks, where energy efficiency is the key design challenge, the energy consumption is typically dominated by the node's communication subsystem. It can only be reduced significantly by transitioning the embedded radio to a sleep state, at which point the node essentially retracts from the network topology. Existing topology management schemes have focused on cleverly selecting which nodes can turn off their radio, without sacrificing the capacity of the network. We propose a new technique, called sparse topology and energy management (STEM), that dramatically improves the network lifetime by exploiting the fact that most of the time, the network is only sensing its environment waiting for an event to happen. By alleviating the restriction of network capacity preservation, we can trade off extensive energy savings for an increased latency to set up a multi-hop path. We will also show how STEM integrates efficiently with existing topology management techniques.

STEM: Topology management for energy efficient sensor networks

Optimizing sensor networks in the energy-density-latency design space

Networks of wireless microsensors for monitoring physical environments have emerged as an important new application area for wireless technology. Key attributes of these new types of networked systems are the severely constrained computational and energy resources, and an ad hoc operational environment. This paper is a study of the communication security aspects of these networks. Resource limitations and specific architecture of sensor networks call for customized security mechanisms. Our approach is to classify the types of data existing in sensor networks, and identify possible communication security threats according to that classification. We propose a communication security scheme where for each type of data we define a corresponding security mechanism. By employing this multitiered security architecture where each mechanism has different resource requirements, we allow for efficient resource management, which is essential for wireless sensor networks.

/pdf/on-communication-security-in-wireless-ad-hoc-sensor-networks-1n0o90aeup.pdf

Vlasios Tsiatsis

Papers

Optimizing sensor networks in the energy-latency-density design space

Topology management for sensor networks: exploiting latency and density

STEM: Topology management for energy efficient sensor networks

Optimizing sensor networks in the energy-density-latency design space

On communication security in wireless ad-hoc sensor networks