Vlasios Tsiatsis

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

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.

STEM: Topology management for energy efficient sensor networks

In wireless sensor networks, where energy efficiency is the key design challenge, the energy consumption is typically dominated by the nodes 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.

On communication security in wireless ad-hoc sensor networks

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.

Estimating clock uncertainty for efficient duty-cycling in sensor networks

Radio duty cycling has received significant attention in sensor networking literature, particularly in the form of protocols for medium access control and topology management. While many protocols have claimed to achieve significant duty-cycling benefits in theory and simulation, these benefits have often not translated into practice. The dominant factor that prevents the optimal usage of the radio in real deployment settings is time uncertainty between sensor nodes which results in overhead in the form of long packet preambles, guard bands, and excessive control packets for synchronization. This paper proposes an uncertainty-driven approach to duty-cycling, where a model of long-term clock drift is used to minimize the duty-cycling overhead. First, we use long-term empirical measurements to evaluate and analyze in-depth the interplay between three key parameters that influence long-term synchronization: synchronization rate, history of past synchronization beacons, and the estimation scheme. Second, we use this measurement-based study to design a rate-adaptive, energy-efficient long-term time synchronization algorithm that can adapt to changing clock drift and environmental conditions, while achieving application-specific precision with very high probability. Finally, we integrate our uncertainty-driven time synchronization scheme with the BMAC medium access control protocol, and demonstrate one to two orders of magnitude reduction in transmission energy consumption with negligible impact on packet loss rate.

Computation hierarchy for in-network processing

In this paper we explore the network level architecture of distributed sensor systems that perform in-network processing. We propose a system with heterogeneous nodes that organizes into a hierarchical structure dictated by the computational capabilities. The presence of high-performance nodes amongst a sea of resource-constrained nodes exposes new tradeoffs for the efficient implementation of network-wide applications. Our experiments show that even for a low relative density of resource-constrained nodes to high-performance nodes there are certain gains in performance for a heterogeneous and hierarchical network over a homogeneous one. The introduction of hierarchy enables partitioning of the application into sub-tasks that can be mapped onto the heterogeneous nodes in the network in multiple ways. We analyze the tradeoffs between the execution time of the application, accuracy of the output produced and the overall energy consumption of the network for the different mapping of the sub-tasks onto the heterogeneous nodes. We evaluate the performance and energy consumption of a typical sensor network application of target tracking via beamforming and line of bearing (LOB) calculations on the different nodes. Our experiments also include the study of the overall performance and energy consumption of the LOB calculation using two different types of resource constrained sensor nodes (MICA and MICA2 nodes) and show how these metrics are affected by changes in the node architecture and operation. Our results indicate that when using MICA motes as resource-constrained nodes, 85% of the time on average the hierarchical network outperforms a homogeneous network for approximately the same energy budget. When using MICA2 motes as resource-constrained nodes, 54% of the time the hierarchical network performs better than a homogeneous network with approximately the same energy budget.

Architecture strategies for energy-efficient packet forwarding in wireless sensor networks

The energy-efficient communication among wireless sensor nodes determines the lifetime of a sensor network and exhibits patterns highly dependable on the sensor application and networking software. This software is responsible for processing the sensor data and disseminating the data to other nodes or a central repository. In this paper we propose a node architecture that takes advantage of both the intelligence of the radio hardware and the needs of applications to efficiently handle the packet forwarding. It exploits principles widely used in modem firewall network architectures and as our analysis shows achieves considerable energy savings.