47,674 research outputs found
Exploiting programmable architectures for WiFi/ZigBee inter-technology cooperation
The increasing complexity of wireless standards has shown that protocols cannot be designed once for all possible deployments, especially when unpredictable and mutating interference situations are present due to the coexistence of heterogeneous technologies. As such, flexibility and (re)programmability of wireless devices is crucial in the emerging scenarios of technology proliferation and unpredictable interference conditions.
In this paper, we focus on the possibility to improve coexistence performance of WiFi and ZigBee networks by exploiting novel programmable architectures of wireless devices able to support run-time modifications of medium access operations. Differently from software-defined radio (SDR) platforms, in which every function is programmed from scratch, our programmable architectures are based on a clear decoupling between elementary commands (hard-coded into the devices) and programmable protocol logic (injected into the devices) according to which the commands execution is scheduled.
Our contribution is two-fold: first, we designed and implemented a cross-technology time division multiple access (TDMA) scheme devised to provide a global synchronization signal and allocate alternating channel intervals to WiFi and ZigBee programmable nodes; second, we used the OMF control framework to define an interference detection and adaptation strategy that in principle could work in independent and autonomous networks. Experimental results prove the benefits of the envisioned solution
Coordination in State-Dependent Distributed Networks: The Two-Agent Case
This paper addresses a coordination problem between two agents (Agents
and ) in the presence of a noisy communication channel which depends on an
external system state . The channel takes as inputs both agents'
actions, and and produces outputs that are observed
strictly causally at Agent but not at Agent . The system state is
available either causally or non-causally at Agent but unknown at Agent
. Necessary and sufficient conditions on a joint distribution
to be implementable asymptotically (i.e, when the number
of taken actions grows large) are provided for both causal and non-causal state
information at Agent .
Since the coordination degree between the agents' actions, and
, and the system state is measured in terms of an average
payoff function, feasible payoffs are fully characterized by implementable
joint distributions. In this sense, our results allow us to derive the
performance of optimal power control policies on an interference channel and to
assess the gain provided by non-causal knowledge of the system state at Agent
.
The derived proofs readily yield new results also for the problem of
state-amplification under a causality constraint at the decoder.Comment: Published in 2015 IEEE International Symposium on Information Theor
Practical applications of multi-agent systems in electric power systems
The transformation of energy networks from passive to active systems requires the embedding of intelligence within the network. One suitable approach to integrating distributed intelligent systems is multi-agent systems technology, where components of functionality run as autonomous agents capable of interaction through messaging. This provides loose coupling between components that can benefit the complex systems envisioned for the smart grid. This paper reviews the key milestones of demonstrated agent systems in the power industry and considers which aspects of agent design must still be addressed for widespread application of agent technology to occur
Object-oriented Tools for Distributed Computing
Distributed computing systems are proliferating, owing to the availability of powerful, affordable microcomputers and inexpensive communication networks. A critical problem in developing such systems is getting application programs to interact with one another across a computer network. Remote interprogram connectivity is particularly challenging across heterogeneous environments, where applications run on different kinds of computers and operating systems. NetWorks! (trademark) is an innovative software product that provides an object-oriented messaging solution to these problems. This paper describes the design and functionality of NetWorks! and illustrates how it is being used to build complex distributed applications for NASA and in the commercial sector
Empirical Coordination with Two-Sided State Information and Correlated Source and State
The coordination of autonomous agents is a critical issue for decentralized
communication networks. Instead of transmitting information, the agents
interact in a coordinated manner in order to optimize a general objective
function. A target joint probability distribution is achievable if there exists
a code such that the sequences of symbols are jointly typical. The empirical
coordination is strongly related to the joint source-channel coding with
two-sided state information and correlated source and state. This problem is
also connected to state communication and is open for non-causal encoder and
decoder. We characterize the optimal solutions for perfect channel, for
lossless decoding, for independent source and channel, for causal encoding and
for causal decoding.Comment: 5 figures, 5 pages, presented at IEEE International Symposium on
Information Theory (ISIT) 201
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