348 research outputs found

    INTERMITTENTLY CONNECTED DELAY-TOLERANT WIRELESS SENSOR NETWORKS

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    Intermittently Connected Delay-Tolerant Wireless Sensor Networks (ICDT-WSNs), a branch of Wireless Sensor Networks (WSNs), have features of WSNs and the intermittent connectivity of Opportunistic Networks. The applications of ICDT-WSNs are increasing in recent years; however, the communication protocols suitable for this category of networks often fall short. Most of the existing communication protocols are designed for either WSNs or Opportunistic Networks with sufficient resources and tend to be inadequate for direct use in ICDT-WSNs. In this dissertation, we study ICDT-WSNs from the perspective of the characteristics, chal- lenges and possible solutions. A high-level overview of ICDT-WSNs is given, followed by a study of existing work and our solutions to address the problems of routing, flow control, error control, and storage management. The proposed solutions utilize the utility level of nodes and the connectedness of a network. In addition to the protocols for information transmissions to specific destinations, we also propose efficient mechanisms for information dissemination to arbitrary destinations. The study shows that our proposed solutions can achieve better performance than other state of the art communication protocols without sacrificing energy efficiency

    Efficient and adaptive congestion control for heterogeneous delay-tolerant networks

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    Detecting and dealing with congestion in delay-tolerant networks (DTNs) is an important and challenging problem. Current DTN forwarding algorithms typically direct traffic towards more central nodes in order to maximise delivery ratios and minimise delays, but as traffic demands increase these nodes may become saturated and unusable. We pro- pose CafRep, an adaptive congestion aware protocol that detects and reacts to congested nodes and congested parts of the network by using implicit hybrid contact and resources congestion heuristics. CafRep exploits localised relative utility based approach to offload the traffic from more to less congested parts of the network, and to replicate at adaptively lower rate in different parts of the network with non-uniform congestion levels. We extensively evaluate our work against benchmark and competitive protocols across a range of metrics over three real connectivity and GPS traces such as Sassy [44], San Francisco Cabs [45] and Infocom 2006 [33]. We show that CafRep performs well, independent of network connectivity and mobility patterns, and consistently outperforms the state-of-the-art DTN forwarding algorithms in the face of increasing rates of congestion. CafRep maintains higher availability and success ratios while keeping low delays, packet loss rates and delivery cost. We test CafRep in the presence of two application scenarios, with fixed rate traffic and with real world Facebook application traffic demands, showing that regardless of the type of traffic CafRep aims to deliver, it reduces congestion and improves forwarding performance

    Practical opportunistic data collection in wireless sensor networks with mobile sinks

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    Wireless Sensor Networks with Mobile Sinks (WSN-MSs) are considered a viable alternative to the heavy cost of deployment of traditional wireless sensing infrastructures at scale. However, current state-of-the-art approaches perform poorly in practice due to their requirement of mobility prediction and specific assumptions on network topology. In this paper, we focus on lowdelay and high-throughput opportunistic data collection in WSN-MSs with general network topologies and arbitrary numbers of mobile sinks. We first propose a novel routing metric, Contact-Aware ETX (CA-ETX), to estimate the packet transmission delay caused by both packet retransmissions and intermittent connectivity. By implementing CA-ETX in the defacto TinyOS routing standard CTP and the IETF IPv6 routing protocol RPL, we demonstrate that CA-ETX can work seamlessly with ETX. This means that current ETXbased routing protocols for static WSNs can be easily extended to WSN-MSs with minimal modification by using CA-ETX. Further, by combing CA-ETX with the dynamic backpressure routing, we present a throughput-optimal scheme Opportunistic Backpressure Collection (OBC). Both CA-ETX and OBC are lightweight, easy to implement, and require no mobility prediction. Through test-bed experiments and extensive simulations, we show that the proposed schemes significantly outperform current approaches in terms of packet transmission delay, communication overhead, storage overheads, reliability, and scalability

    A Distance-Aware Replica Adaptive Data Gathering Protocol for Delay Tolerant Mobile Sensor Networks

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    In Delay Tolerant Mobile Sensor Networks (DTMSNs) that have the inherent features of intermitted connectivity and frequently changing network topology it is reasonable to utilize multi-replica schemes to improve the data gathering performance. However, most existing multi-replica approaches inject a large amount of message copies into the network to increase the probability of message delivery, which may drain each mobile node’s limited battery supply faster and result in too much contention for the restricted resources of the DTMSN, so a proper data gathering scheme needs a trade off between the number of replica messages and network performance. In this paper, we propose a new data gathering protocol called DRADG (for Distance-aware Replica Adaptive Data Gathering protocol), which economizes network resource consumption through making use of a self-adapting algorithm to cut down the number of redundant replicas of messages, and achieves a good network performance by leveraging the delivery probabilities of the mobile sensors as main routing metrics. Simulation results have shown that the proposed DRADG protocol achieves comparable or higher message delivery ratios at the cost of the much lower transmission overhead than several current DTMSN data gathering schemes

    Message Forwarding and Scheduling in Delay Tolerant Networks

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    Delay-tolerant networking (DTN) has recently received considerable attention from the research community. This type of networks is characterized by frequent disconnections due to propagation phenomena, node mobility, and power outages. Thus, the complete path between the source and the destination may never have existed. This context requires the design of new communication paradigms and techniques that will make communication possible in these environments. To achieve message delivery, researchers have proposed the use of store-carry-and-forward protocols, whereby a node may store the message and carry it until an appropriate forwarding opportunity arises. Many flooding-routing schemes have been proposed for DTNs in order to increase the probability of message delivery. However, these schemes suffer from excessive energy consumption, severe contention that significantly degrades their performance, especially if we account for the fact that each node could be a hand-held and battery-powered device with stringent buffer size limitation. With such buffer limitations at the DTN nodes, message drop/loss could happen due to buffer overflow. In order to address the problem and improve the performance of DTNs, this thesis focuses on two main design objectives; first, the design and evaluation of new multi-copy routing schemes; second, the design and evaluation of new scheduling and dropping policies to reduce message drop/loss due to buffer overflow. To fulfill the first objective, a protocol called Self Adaptive Routing Protocol (SARP) is introduced. It is a multi-copy scheme designed to suit resource-sufficient DTNs. Based on SARP, two multi-copy routing schemes are further developed to suit resource-limited DTNs, in which compensating the traffic demand become a challenge: i) the Self Adaptive Utility-based Routing Protocol (SAURP), ii) and the Adaptive Reinforcement based Routing Protocol (ARBRP). The introduced protocols form a new framework of DTNs aiming to significantly reduce the resource requirements of flooding-based routing schemes. Each introduced scheme has its own way of exploring the possibility of taking mobile nodes as message carriers in order to increase the delivery ratio of the messages. In SAURP, the best carrier for a message characterized by jointly considering the inter-contact time that is obtained using a novel contact model and the network status, such as including wireless link condition and nodal buffer availability. In ARBRP, the routing problem is solved by manipulating a collaborative reinforcement learning technique, where a group of nodes can cooperate with each other to make a forwarding decision for the stored messages based on a cost function at each contact with another node. ARBRP is characterized by not only considering the contact time statistics, but also looks into the feedback on user behavior and network conditions, such as congestion and buffer occupancy sampled during each previous contact with any other node. The thesis argues and proves that the nodal movement and the predicted collocation with the message recipient can serve as meaningful information to achieve an intelligent message forwarding decision at each node. Therefore, the introduced protocols can achieve high efficiency via an adaptive and intelligent routing mechanism according to network conditions. To fulfill the second objective, we further enhanced the performance of DTN routing by introducing message scheduling and dropping policies such that the delivery ratio is increased and/or the delivery delay is reduced. This thesis investigates new buffer management and scheduling policies to improve the performance of flooding and utility-based forwarding routing in DTNs, such that the forwarding/dropping decision can be made at a node during each contact for either optimal message delivery ratio or message delivery delay. To examine their effectiveness, the introduced protocols and the buffer management and scheduling policies have been implemented and compared to a number of existing counterpart approaches. A near-realistic mobility model is used for testing. A number of scenarios are used to evaluate the performance of the introduced techniques in terms of delivery delay, ratio, and the number of transmissions performed

    Socio-economic aware data forwarding in mobile sensing networks and systems

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    The vision for smart sustainable cities is one whereby urban sensing is core to optimising city operation which in turn improves citizen contentment. Wireless Sensor Networks are envisioned to become pervasive form of data collection and analysis for smart cities but deployment of millions of inter-connected sensors in a city can be cost-prohibitive. Given the ubiquity and ever-increasing capabilities of sensor-rich mobile devices, Wireless Sensor Networks with Mobile Phones (WSN-MP) provide a highly flexible and ready-made wireless infrastructure for future smart cities. In a WSN-MP, mobile phones not only generate the sensing data but also relay the data using cellular communication or short range opportunistic communication. The largest challenge here is the efficient transmission of potentially huge volumes of sensor data over sometimes meagre or faulty communications networks in a cost-effective way. This thesis investigates distributed data forwarding schemes in three types of WSN-MP: WSN with mobile sinks (WSN-MS), WSN with mobile relays (WSN-HR) and Mobile Phone Sensing Systems (MPSS). For these dynamic WSN-MP, realistic models are established and distributed algorithms are developed for efficient network performance including data routing and forwarding, sensing rate control and and pricing. This thesis also considered realistic urban sensing issues such as economic incentivisation and demonstrates how social network and mobility awareness improves data transmission. Through simulations and real testbed experiments, it is shown that proposed algorithms perform better than state-of-the-art schemes.Open Acces
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