22,800 research outputs found
Energy efficient privacy preserved data gathering in wireless sensor networks having multiple sinks
Wireless sensor networks (WSNs) generally have a many-to-one structure so that event information flows from sensors to a unique sink. In recent WSN applications, many-tomany structures are evolved due to need for conveying collected event information to multiple sinks at the same time. This study proposes an anonymity method bases on k-anonymity for preventing record disclosure of collected event information in WSNs. Proposed method takes the anonymity requirements of multiple sinks into consideration by providing different levels of privacy for each destination sink. Attributes, which may identify of an event owner, are generalized or encrypted in order to
meet the different anonymity requirements of sinks. Privacy guaranteed event information can be multicasted to all sinks instead of sending to each sink one by one. Since minimization of energy consumption is an important design criteria for WSNs, our method enables us to multicast the same event information
to multiple sinks and reduce energy consumption
A Faster Counting Protocol for Anonymous Dynamic Networks
We study the problem of counting the number of nodes in a slotted-time
communication network, under the challenging assumption that nodes do not have
identifiers and the network topology changes frequently. That is, for each time
slot links among nodes can change arbitrarily provided that the network is
always connected. Tolerating dynamic topologies is crucial in face of mobility
and unreliable communication whereas, even if identifiers are available, it
might be convenient to ignore them in massive networks with changing topology.
Counting is a fundamental task in distributed computing since knowing the size
of the system often facilitates the design of solutions for more complex
problems. Currently, the best upper bound proved on the running time to compute
the exact network size is double-exponential. However, only linear complexity
lower bounds are known, leaving open the question of whether efficient Counting
protocols for Anonymous Dynamic Networks exist or not. In this paper we make a
significant step towards answering this question by presenting a distributed
Counting protocol for Anonymous Dynamic Networks which has exponential time
complexity. Our algorithm ensures that eventually every node knows the exact
size of the system and stops executing the algorithm. Previous Counting
protocols have either double-exponential time complexity, or they are
exponential but do not terminate, or terminate but do not provide running-time
guarantees, or guarantee only an exponential upper bound on the network size.
Other protocols are heuristic and do not guarantee the correct count
Distributed anonymous function computation in information fusion and multiagent systems
We propose a model for deterministic distributed function computation by a
network of identical and anonymous nodes, with bounded computation and storage
capabilities that do not scale with the network size. Our goal is to
characterize the class of functions that can be computed within this model. In
our main result, we exhibit a class of non-computable functions, and prove that
every function outside this class can at least be approximated. The problem of
computing averages in a distributed manner plays a central role in our
development
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