11,445 research outputs found
A system-theoretic framework for privacy preservation in continuous-time multiagent dynamics
In multiagent dynamical systems, privacy protection corresponds to avoid
disclosing the initial states of the agents while accomplishing a distributed
task. The system-theoretic framework described in this paper for this scope,
denoted dynamical privacy, relies on introducing output maps which act as
masks, rendering the internal states of an agent indiscernible by the other
agents as well as by external agents monitoring all communications. Our output
masks are local (i.e., decided independently by each agent), time-varying
functions asymptotically converging to the true states. The resulting masked
system is also time-varying, and has the original unmasked system as its limit
system. When the unmasked system has a globally exponentially stable
equilibrium point, it is shown in the paper that the masked system has the same
point as a global attractor. It is also shown that existence of equilibrium
points in the masked system is not compatible with dynamical privacy.
Application of dynamical privacy to popular examples of multiagent dynamics,
such as models of social opinions, average consensus and synchronization, is
investigated in detail.Comment: 38 pages, 4 figures, extended version of arXiv preprint
arXiv:1808.0808
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
DDH-MAC: a novel dynamic de-centralized hybrid MAC protocol for cognitive radio networks
The radio spectrum (3kHz - 300GHz) has become saturated and proven to be insufficient to address the proliferation of new wireless applications. Cognitive Radio Technology which is an opportunistic network and is equipped with fully programmable wireless devices that empowers the network by OODA cycle and then make intelligent decisions by adapting their MAC and physical layer characteristics such as waveform, has appeared to be the only solution for current low spectrum availability and under utilization problem. In this paper a novel Dynamic De-Centralized Hybrid “DDH-MAC” protocol for Cognitive Radio Networks has been presented which lies between Global Common Control Channel (GCCC) and non-GCCC categories of cognitive radio MAC protocols. DDH-MAC is equipped with the best features of GCCC MAC protocols but also overcomes the saturation and security issues in GCCC. To the best of authors' knowledge, DDH-MAC is the first protocol which is hybrid between GCCC and non-GCCC family of protocols. DDH-MAC provides multiple levels of security and partially use GCCC to transmit beacon which sets and announces local control channel for exchange of free channel list (FCL) sensed by the co-operatively communicating cognitive radio nodes, subsequently providing secure transactions among participating nodes over the decided local control channel. This paper describes the framework of the DDH-MAC protocol in addition to its pseudo code for implementation; it is shown that the pre-transmission time for DDH-MAC is on average 20% better while compared to other cognitive radio MAC protocols
BAN-GZKP: Optimal Zero Knowledge Proof based Scheme for Wireless Body Area Networks
BANZKP is the best to date Zero Knowledge Proof (ZKP) based secure
lightweight and energy efficient authentication scheme designed for Wireless
Area Network (WBAN). It is vulnerable to several security attacks such as the
replay attack, Distributed Denial-of-Service (DDoS) attacks at sink and
redundancy information crack. However, BANZKP needs an end-to-end
authentication which is not compliant with the human body postural mobility. We
propose a new scheme BAN-GZKP. Our scheme improves both the security and
postural mobility resilience of BANZKP. Moreover, BAN-GZKP uses only a
three-phase authentication which is optimal in the class of ZKP protocols. To
fix the security vulnerabilities of BANZKP, BAN-GZKP uses a novel random key
allocation and a Hop-by-Hop authentication definition. We further prove the
reliability of our scheme to various attacks including those to which BANZKP is
vulnerable. Furthermore, via extensive simulations we prove that our scheme,
BAN-GZKP, outperforms BANZKP in terms of reliability to human body postural
mobility for various network parameters (end-to-end delay, number of packets
exchanged in the network, number of transmissions). We compared both schemes
using representative convergecast strategies with various transmission rates
and human postural mobility. Finally, it is important to mention that BAN-GZKP
has no additional cost compared to BANZKP in terms memory, computational
complexity or energy consumption
Middleware Technologies for Cloud of Things - a survey
The next wave of communication and applications rely on the new services
provided by Internet of Things which is becoming an important aspect in human
and machines future. The IoT services are a key solution for providing smart
environments in homes, buildings and cities. In the era of a massive number of
connected things and objects with a high grow rate, several challenges have
been raised such as management, aggregation and storage for big produced data.
In order to tackle some of these issues, cloud computing emerged to IoT as
Cloud of Things (CoT) which provides virtually unlimited cloud services to
enhance the large scale IoT platforms. There are several factors to be
considered in design and implementation of a CoT platform. One of the most
important and challenging problems is the heterogeneity of different objects.
This problem can be addressed by deploying suitable "Middleware". Middleware
sits between things and applications that make a reliable platform for
communication among things with different interfaces, operating systems, and
architectures. The main aim of this paper is to study the middleware
technologies for CoT. Toward this end, we first present the main features and
characteristics of middlewares. Next we study different architecture styles and
service domains. Then we presents several middlewares that are suitable for CoT
based platforms and lastly a list of current challenges and issues in design of
CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268,
Digital Communications and Networks, Elsevier (2017
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