10,242 research outputs found
Stochastic Analysis of a Churn-Tolerant Structured Peer-to-Peer Scheme
We present and analyze a simple and general scheme to build a churn
(fault)-tolerant structured Peer-to-Peer (P2P) network. Our scheme shows how to
"convert" a static network into a dynamic distributed hash table(DHT)-based P2P
network such that all the good properties of the static network are guaranteed
with high probability (w.h.p). Applying our scheme to a cube-connected cycles
network, for example, yields a degree connected network, in which
every search succeeds in hops w.h.p., using messages,
where is the expected stable network size. Our scheme has an constant
storage overhead (the number of nodes responsible for servicing a data item)
and an overhead (messages and time) per insertion and essentially
no overhead for deletions. All these bounds are essentially optimal. While DHT
schemes with similar guarantees are already known in the literature, this work
is new in the following aspects:
(1) It presents a rigorous mathematical analysis of the scheme under a
general stochastic model of churn and shows the above guarantees;
(2) The theoretical analysis is complemented by a simulation-based analysis
that validates the asymptotic bounds even in moderately sized networks and also
studies performance under changing stable network size;
(3) The presented scheme seems especially suitable for maintaining dynamic
structures under churn efficiently. In particular, we show that a spanning tree
of low diameter can be efficiently maintained in constant time and logarithmic
number of messages per insertion or deletion w.h.p.
Keywords: P2P Network, DHT Scheme, Churn, Dynamic Spanning Tree, Stochastic
Analysis
An Architecture for Distributed Energies Trading in Byzantine-Based Blockchain
With the development of smart cities, not only are all corners of the city
connected to each other, but also connected from city to city. They form a
large distributed network together, which can facilitate the integration of
distributed energy station (DES) and corresponding smart aggregators.
Nevertheless, because of potential security and privacy protection arisen from
trustless energies trading, how to make such energies trading goes smoothly is
a tricky challenge. In this paper, we propose a blockchain-based multiple
energies trading (B-MET) system for secure and efficient energies trading by
executing a smart contract we design. Because energies trading requires the
blockchain in B-MET system to have high throughput and low latency, we design a
new byzantine-based consensus mechanism (BCM) based on node's credit to improve
efficiency for the consortium blockchain under the B-MET system. Then, we take
combined heat and power (CHP) system as a typical example that provides
distributed energies. We quantify their utilities, and model the interactions
between aggregators and DESs in a smart city by a novel multi-leader
multi-follower Stackelberg game. It is analyzed and solved by reaching Nash
equilibrium between aggregators, which reflects the competition between
aggregators to purchase energies from DESs. In the end, we conduct plenty of
numerical simulations to evaluate and verify our proposed model and algorithms,
which demonstrate their correctness and efficiency completely
Bold:Bio-inspired optimized leader election for multiple drones
Over the past few years, unmanned aerial vehicles (UAV) or drones have been used for many applications. In certain applications like surveillance and emergency rescue operations, multiple drones work as a network to achieve the target in which any one of the drones will act as the master or coordinator to communicate, monitor, and control other drones. Hence, drones are energy-constrained; there is a need for effective coordination among them in terms of decision making and communication between drones and base stations during these critical situations. This paper focuses on providing an efficient approach for the election of the cluster head dynamically, which heads the other drones in the network. The main objective of the paper is to provide an effective solution to elect the cluster head among multi drones at different periods based on the various physical constraints of drones. The elected cluster head acts as the decision-maker and assigns tasks to other drones. In a case where the cluster head fails, then the next eligible drone is re-elected as the leader. Hence, an optimally distributed solution proposed is called Bio-Inspired Optimized Leader Election for Multiple Drones (BOLD), which is based on two AI-based optimization techniques. The simulation results of BOLD compared with the existing Particle Swarm Optimization-Cluster head election (PSO-C) in terms of network lifetime and energy consumption, and from the results, it has been proven that the lifetime of drones with the BOLD algorithm is 15% higher than the drones with PSO-C algorithm
Generic Platform for Failure Recovery in Survivable Trees
Failure recovery is a fundamental task of the dependable systems needed to achieve fault-tolerant communications, smooth operation of system components and a comfortable user interface. Tree topologies are fragile, yet they are quite popular structures in computer systems. The term survivable tree denotes the capability of the tree network to deliver messages even in the presence of failures. In this paper, we analyze the characteristics of large-scale overlay survivable trees and identify the requirements for general-purpose failure recovery mechanisms in such an environment. We outline a generic failure recovery platform for preplanned tree restoration which meets those requirements, and we focus primarily on its completeness and correctness properties. The platform is based on bypass rings and it uses a bypass routing algorithm to ensure completeness, and specialized leader election to guarantee correctness. The platform supports multiple, on-line and on-the-fly recovery, provides an optional level of fault-tolerance, protection selectivity and optimization capability. It is independent of the the protected tree type (regarding traffic direction, number of sources, etc.) and forms a basis for application-specific fragment reconnection.
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