4,408 research outputs found
In Vivo Evaluation of the Secure Opportunistic Schemes Middleware using a Delay Tolerant Social Network
Over the past decade, online social networks (OSNs) such as Twitter and
Facebook have thrived and experienced rapid growth to over 1 billion users. A
major evolution would be to leverage the characteristics of OSNs to evaluate
the effectiveness of the many routing schemes developed by the research
community in real-world scenarios. In this paper, we showcase the Secure
Opportunistic Schemes (SOS) middleware which allows different routing schemes
to be easily implemented relieving the burden of security and connection
establishment. The feasibility of creating a delay tolerant social network is
demonstrated by using SOS to power AlleyOop Social, a secure delay tolerant
networking research platform that serves as a real-life mobile social
networking application for iOS devices. SOS and AlleyOop Social allow users to
interact, publish messages, and discover others that share common interests in
an intermittent network using Bluetooth, peer-to-peer WiFi, and infrastructure
WiFi.Comment: 6 pages, 4 figures, accepted in ICDCS 2017. arXiv admin note: text
overlap with arXiv:1702.0565
Performance Evaluation of Caching Policies in NDN - an ICN Architecture
Information Centric Networking (ICN) advocates the philosophy of accessing
the content independent of its location. Owing to this location independence in
ICN, the routers en-route can be enabled to cache the content to serve the
future requests for the same content locally. Several ICN architectures have
been proposed in the literature along with various caching algorithms for
caching and cache replacement at the routers en-route. The aim of this paper is
to critically evaluate various caching policies using Named Data Networking
(NDN), an ICN architecture proposed in literature. We have presented the
performance comparison of different caching policies naming First In First Out
(FIFO), Least Recently Used (LRU), and Universal Caching (UC) in two network
models; Watts-Strogatz (WS) model (suitable for dense short link networks such
as sensor networks) and Sprint topology (better suited for large Internet
Service Provider (ISP) networks) using ndnSIM, an ns3 based discrete event
simulator for NDN architecture. Our results indicate that UC outperforms other
caching policies such as LRU and FIFO and makes UC a better alternative for
both sensor networks and ISP networks
Pervasive intelligent routing in content centric delay tolerant networks
This paper introduces a Swarm-Intelligence based Routing protocol (SIR) that aims to efficiently route information in content centric Delay Tolerant Networks (CCDTN) also dubbed pocket switched networks. First, this paper formalizes the notion of optimal path in CCDTN and introduces an original and efficient algorithm to process these paths in dynamic graphs. The properties and some invariant features of these optimal paths are analyzed and derived from several real traces. Then, this paper shows how optimal path in CCDTN can be found and used from a fully distributed swarm-intelligence based approach of which the global intelligent behavior (i.e. shortest path discovery and use) emerges from simple peer to peer interactions applied during opportunistic contacts. This leads to the definition of the SIR routing protocol of which the consistency, efficiency and performances are demonstrated from intensive representative simulations
Wireless Communications in the Era of Big Data
The rapidly growing wave of wireless data service is pushing against the
boundary of our communication network's processing power. The pervasive and
exponentially increasing data traffic present imminent challenges to all the
aspects of the wireless system design, such as spectrum efficiency, computing
capabilities and fronthaul/backhaul link capacity. In this article, we discuss
the challenges and opportunities in the design of scalable wireless systems to
embrace such a "bigdata" era. On one hand, we review the state-of-the-art
networking architectures and signal processing techniques adaptable for
managing the bigdata traffic in wireless networks. On the other hand, instead
of viewing mobile bigdata as a unwanted burden, we introduce methods to
capitalize from the vast data traffic, for building a bigdata-aware wireless
network with better wireless service quality and new mobile applications. We
highlight several promising future research directions for wireless
communications in the mobile bigdata era.Comment: This article is accepted and to appear in IEEE Communications
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