1,075 research outputs found
Amorphous Placement and Retrieval of Sensory Data in Sparse Mobile Ad-Hoc Networks
AbstractâPersonal communication devices are increasingly being equipped with sensors that are able to passively collect information from their surroundings â information that could be stored in fairly small local caches. We envision a system in which users of such devices use their collective sensing, storage, and communication resources to query the state of (possibly remote) neighborhoods. The goal of such a system is to achieve the highest query success ratio using the least communication overhead (power). We show that the use of Data Centric Storage (DCS), or directed placement, is a viable approach for achieving this goal, but only when the underlying network is well connected. Alternatively, we propose, amorphous placement, in which sensory samples are cached locally and informed exchanges of cached samples is used to diffuse the sensory data throughout the whole network. In handling queries, the local cache is searched first for potential answers. If unsuccessful, the query is forwarded to one or more direct neighbors for answers. This technique leverages node mobility and caching capabilities to avoid the multi-hop communication overhead of directed placement. Using a simplified mobility model, we provide analytical lower and upper bounds on the ability of amorphous placement to achieve uniform field coverage in one and two dimensions. We show that combining informed shuffling of cached samples upon an encounter between two nodes, with the querying of direct neighbors could lead to significant performance improvements. For instance, under realistic mobility models, our simulation experiments show that amorphous placement achieves 10% to 40% better query answering ratio at a 25% to 35% savings in consumed power over directed placement.National Science Foundation (CNS Cybertrust 0524477, CNS NeTS 0520166, CNS ITR 0205294, EIA RI 0202067
An Authentication Protocol for Future Sensor Networks
Authentication is one of the essential security services in Wireless Sensor
Networks (WSNs) for ensuring secure data sessions. Sensor node authentication
ensures the confidentiality and validity of data collected by the sensor node,
whereas user authentication guarantees that only legitimate users can access
the sensor data. In a mobile WSN, sensor and user nodes move across the network
and exchange data with multiple nodes, thus experiencing the authentication
process multiple times. The integration of WSNs with Internet of Things (IoT)
brings forth a new kind of WSN architecture along with stricter security
requirements; for instance, a sensor node or a user node may need to establish
multiple concurrent secure data sessions. With concurrent data sessions, the
frequency of the re-authentication process increases in proportion to the
number of concurrent connections, which makes the security issue even more
challenging. The currently available authentication protocols were designed for
the autonomous WSN and do not account for the above requirements. In this
paper, we present a novel, lightweight and efficient key exchange and
authentication protocol suite called the Secure Mobile Sensor Network (SMSN)
Authentication Protocol. In the SMSN a mobile node goes through an initial
authentication procedure and receives a re-authentication ticket from the base
station. Later a mobile node can use this re-authentication ticket when
establishing multiple data exchange sessions and/or when moving across the
network. This scheme reduces the communication and computational complexity of
the authentication process. We proved the strength of our protocol with
rigorous security analysis and simulated the SMSN and previously proposed
schemes in an automated protocol verifier tool. Finally, we compared the
computational complexity and communication cost against well-known
authentication protocols.Comment: This article is accepted for the publication in "Sensors" journal. 29
pages, 15 figure
Strengths and Weaknesses of Prominent Data Dissemination Techniques in Wireless Sensor Networks
Data dissemination is the most significant task in a Wireless Sensor Network (WSN). From the bootstrapping stage to the full functioning stage, a WSN must disseminate data in various patterns like from the sink to node, from node to sink, from node to node, or the like. This is what a WSN is deployed for. Hence, this issue comes with various data routing models and often there are different types of network settings that influence the way of data collection and/or distribution. Considering the importance of this issue, in this paper, we present a survey on various prominent data dissemination techniques in such network. Our classification of the existing works is based on two main parameters: the number of sink (single or multiple) and the nature of its movement (static or mobile). Under these categories, we have analyzed various previous works for their relative strengths and weaknesses. A comparison is also made based on the operational methods of various data dissemination schemes
Game Theory-Based Cooperation for Underwater Acoustic Sensor Networks: Taxonomy, Review, Research Challenges and Directions.
Exploring and monitoring the underwater world using underwater sensors is drawing a lot of attention these days. In this field cooperation between acoustic sensor nodes has been a critical problem due to the challenging features such as acoustic channel failure (sound signal), long propagation delay of acoustic signal, limited bandwidth and loss of connectivity. There are several proposed methods to improve cooperation between the nodes by incorporating information/game theory in the node's cooperation. However, there is a need to classify the existing works and demonstrate their performance in addressing the cooperation issue. In this paper, we have conducted a review to investigate various factors affecting cooperation in underwater acoustic sensor networks. We study various cooperation techniques used for underwater acoustic sensor networks from different perspectives, with a concentration on communication reliability, energy consumption, and security and present a taxonomy for underwater cooperation. Moreover, we further review how the game theory can be applied to make the nodes cooperate with each other. We further analyze different cooperative game methods, where their performance on different metrics is compared. Finally, open issues and future research direction in underwater acoustic sensor networks are highlighted
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
On-Demand Information Retrieval in Sensor Networks with Localised Query and Energy-Balanced Data Collection
On-demand information retrieval enables users to query and collect up-to-date sensing information from sensor nodes. Since high energy efficiency is required in a sensor network, it is desirable to disseminate query messages with small traffic overhead and to collect sensing data with low energy consumption. However, on-demand query messages are generally forwarded to sensor nodes in network-wide broadcasts, which create large traffic overhead. In addition, since on-demand information retrieval may introduce intermittent and spatial data collections, the construction and maintenance of conventional aggregation structures such as clusters and chains will be at high cost. In this paper, we propose an on-demand information retrieval approach that exploits the name resolution of data queries according to the attribute and location of each sensor node. The proposed approach localises each query dissemination and enable localised data collection with maximised aggregation. To illustrate the effectiveness of the proposed approach, an analytical model that describes the criteria of sink proxy selection is provided. The evaluation results reveal that the proposed scheme significantly reduces energy consumption and improves the balance of energy consumption among sensor nodes by alleviating heavy traffic near the sink
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