Efficient data-forwarding method in delay-tolerant P2P networking for IoT services

These days Internet of Things (IoT), which consists of smart objects such as sensor nodes is the most important technology for providing intelligent services. In the IoT ecosystem, wireless sensor networks deliver collected information from IoT devices to a server via sink nodes, and IoT services are provided by peer-to-peer (P2P) networking between the server and the IoT devices. Particularly, IoT applications with wide service area requires the mobile sink nodes to cover the service area. To employ mobile sink nodes, the network adopts delay-tolerant capability by which delay-tolerant nodes try to transmit data when they connect to the mobile sink node in the application service field. However, if the connection status between a IoT device and a mobile sink node is not good, the efficiency of data forwarding will be decreased. In addition, retransmission in bad connection cause high energy consumption for data transmission. Therefore, data forwarding in the delay-tolerant based services needs to take the connection status into account. The proposed method predicts the connection status using naïve Bayesian classifier and determines whether the delay tolerant node transmits data to the mobile sink node or not. Furthermore, the efficiency of the proposed method was validated through extensive computer simulations.     

Perceiving who and when to leverage data delivery for maritime networks: An optimal stopping view

The advances in the integration of wireless communication and sensor technologies have stimulated an innovative paradigm named Crowd Sensing Networks, which caters to the exponential growth of service demands on the sea and drives the development of potential maritime wideband networks. This paper investigates the issue of sensed traffic data scheduling between vessels, combining Time Division Long Term Evolution (TD-LTE) and delay-tolerant networks (DTNs) on the sea. Specially, we propose a unique network topology which combines maritime crowd sensing network and delay tolerant networks, i.e., a store-carry-and-forward routing topology is explored to address the intermittent network connectivity in maritime context. Notably, the alternative eco-friendly green energy in maritime environment will make the scheduling issue more challenging. To the best of our knowledge, this is the first work to do such investigation with the goal of minimizing the costs associated with end-to-end delay of data delivery and energy consumption of DTN throw box. On this basis, we design the scheme of data cooperation transmission between vessels that the hosting vessel decides which DTN throw box to store the data, and when a vessel arrives, the DTN throw box determines whether to stop, i.e., let the arriving vessel carry the data, or skip it and continue to wait for other vessels. A Two-step Time and Energy Oriented Optimal-stopping (TTEOO) algorithm leveraging backward induction method is proposed, based on the optimal stopping rules. Simulation results are presented to show the effectiveness of the proposed method, in terms of consumption cost and data delivery ratio.     

On mitigating hotspots to maximize network lifetime in multi-hop wireless sensor network with guaranteed transport delay and reliability

In wireless sensor networks (WSNs), sensor nodes close to the sink consume more energy than others because they are burdened with heavier relay traffic destined for the sink and trend to die early, forming hotspots or energy holes in WSNs. It has a serious impact on network lifetime. In this paper, three optimization algorithms are proposed to mitigate hotspots and prolong network lifetime for adaptive Mary Phase Shift Keying (MPSK) based wireless sensor networks while transport delay and reliability can be still guaranteed. Based on the insight gained into the relationship between nodal data load and energy consumption in different regions, the first algorithm (GlobalSame) can extend considerably the network lifetime by selecting the optimal nodal transmission radius r, bit error rate ε and transmission rate allocations in bits per symbol (BPS) τ. The second algorithm (RingSame) can further improve network lifetime by comparison to the GlobalSame algorithm, which by selecting different ε _i and τ _i for nodes in different regions under constraints of total BER and transport delay . While the third algorithm (NodeDiff) can further improve the network lifetime by adopting different BER ε and BPS τ parameters of the same node for data packets received according to its distance to the sink. Extensive simulation studies show that our algorithms do considerably prolong the network lifetime.     

Dynamic duty cycle and adaptive contention window based QoS-MAC protocol for wireless multimedia sensor networks

Rapid penetration of small, customized wireless devices and enormous growth of wireless communication technologies has already set the stage for large-scale deployment of wireless sensor networks. While the need to minimize the energy consumption has driven significant researches in wireless sensor networks, offering some precise quality of service (QoS) for multimedia transmission over sensor networks has not received significant attention. However, the emerging new applications like video surveillance, telemedicine and traffic monitoring needs transmission of wireless multimedia over sensor networks. Naturally, offering some better QoS for wireless multimedia over sensor networks raises significant challenges. The network needs to cope up with battery-constraints, while providing improved QoS (end-to-end delay and bandwidth requirement). This calls for a suitable sensory MAC protocol capable of achieving application-specific QoS. In this paper, we have proposed a new QoS-based sensory MAC protocol, which not only adapts to application-oriented QoS, but also attempts to conserve energy without violating QoS-constraints. Performance modeling, analysis and simulation results demonstrate that the proposed protocol is capable of providing lower delay and better throughput, at the cost of reasonable energy consumption, in comparison to other existing sensory MAC protocols.     

A virtual infrastructure for large-scale wireless sensor networks

The primary goal of a wireless sensor network is to collect useful information from the network. Most wireless sensor networks are assumed that the number of nodes are very large and they should operate with confined resources. Consequently it is important to take a scalable and energy-efficient architecture.In this paper, we present Railroad, a data collection and topology management architecture for large-scale wireless sensor networks. It proactively exploits a virtual infrastructure called Rail, which acts as a rendezvous area of the event data and queries. By using Rail, Railroad achieves scalability and energy efficiency under dynamic conditions with multiple mobile observers and targets. We evaluate the communication cost and the hot area message complexity of Railroad and compare them with previous approaches. We evaluate communication cost of Railroad by both an analytic model and simulations.     

无线传感器网络中基于模型拟合的可信近似查询处理算法

无线传感器网络的一个重要应用是可信地查询网络中所有节点的监测数据.目前,多数研究主要集中在如何利用节点之间的时空相关性,节省能量地查询感知数据.但是这些方法的查询结果不能满足某些应用对数据的高可信要求,也不能适用于节点之间不存在空间相关性或空间相关性不稳定的情况.针对这一问题,提出了基于模型拟合的可信近似查询处理方法.该方法在感知数据集合上寻找具有最小数据传输比的拟合模型,通过传输模型及其参数来代替传输实际的监测数据.理论分析和实验结果证明,基于模型拟合的可信近似查询处理方法不仅能够节省大量能源而且能够返回满足用户精度要求的可信查询结果.     

一种无线传感器网络蚁群优化路由算法

如何在资源受限的无线传感器网络中进行高效的数据路由是无线传感器网络研究的热点之一.将蚁群优化算法(ACO)应用于无线传感器网络的路由,提出一种无线传感器网络蚁群优化路由算法.该算法利用蚁群的自组织、自适应和动态寻优能力进行网络优化路径的建立与维护,采用Stigmergy的概念来减少控制信息的流量,以实现网络数据的高效传输.仿真分析表明,该算法和DD算法相比在传输延时方面性能相当,在路由代价方面效果显著.另外,该算法还具有可靠性高、适应性强等优点,并能够根据需要实现网络的拥堵控制和能量均衡等综合优化.     

能量捕获无线传感器网络中速率自适应路由算法

能量捕获无线传感器网络是无源感知技术中非常重要的一类,它能够有效解决节点能量受限的问题,保持网络运行的持续性.现有的路由方法并未充分利用节点的能量捕获特性,也没有考虑到链路的成功收包率和节点的传输速率.为进一步提高网络的性能,提出了一种结合链路成功收包率的速率自适应路由算法.通过对节点的剩余能量和链路的成功收包率进行建模,给出了一个节点可作为路由中继节点所需要满足的两个条件;基于优化方程,为传输路径上的每一跳节点自适应配置时延最小化的传输速率;提出路由发现步骤来找出端到端传输时延最小的传输路径.实验结果表明,相比于固定传输速率的路由算法,所提算法所得到的传输路径具有较低的端到端传输时延和较高的吞吐率.     

Data forwarding based on sensor device constraints in wireless multimedia sensor networks

A variety of data forwarding schemes have been proposed for wireless multimedia sensor networks where energy awareness and reliability are essential design issues. This paper proposes a data forwarding mechanism based on sensor device constraints in wireless multimedia sensor networks. A dynamic path cost function is defined considering the constraints and characteristics of wireless multimedia sensor networks. The cost function is applied to ZigBee mesh routing, and the performance of the proposed method is evaluated using a QualNet network simulator.     

Fuzzy topology discovery protocol for SDN-based wireless sensor networks

The growing trend in pervasive systems forces traditional wireless sensor networks to deal with new challenges, such as dynamic application requirements and heterogeneous networks. One of the latest paradigms in this area is software defined wireless sensor network. According to the paradigm, the networks take care of managing topological information and forwarding decisions using a bipartite architecture in which a control plane decides the forwarding policies and the data plane (i.e. ordinary sensor nodes) executes them. Unfortunately, in highly dynamic networks, this approach generates an overhead of control packet exchange between the ordinary nodes and the control plane, that leads to additional energy consumptions. This paper proposes a fuzzy logic based solution, called Fuzzy Topology Discovery Protocol (FTDP), to improve the efficiency of software defined wireless sensor networks. This work is designed according to the Software Defined Networking solution for WIreless SEnsor networks (SDN-WISE), which is an open source solution for software defined wireless sensor networks. The proposed work is one of the first attempts to use fuzzy theory in software defined based wireless sensor networks. The simulation results show that our approach can increase the lifetime of the network by 45% and decreases the packet loss ratio by 50% compared to the basic SDN-WISE solution.     

基于功率调节的IWSN实时可靠路由研究

针对工业无线传感器网络对延迟、可靠传输以及成本的特殊要求,研究了一种基于功率调节的实时可靠路由协议,将两跳速度策略引入到路由算法中,提高工业无线传感器网络的实时性;将节点剩余能量以及能耗同时考虑,以平衡网络能量并提高网络寿命;引入功率调节机制以绕开路由空洞,提高节点可靠性.仿真结果显示,与已有方法相比,采用的方法在总可靠度、截止期错失率以及包平均延迟上有着显著改善.     

基于预测的传感器网络副本自适应控制机制

最小跳数路由无线传感器网络具有自动倾向于路径最短、时延最小、能量最省的潜在优点,但已有机制尚不能保证这些优点的充分发挥.为充分发挥最小跳数路由无线传感器网络的潜在优势,在传统的最小跳数路由无线传感器网络数据汇聚机制的基础上,引入基于预测的自适应数据副本保证与抑制机制,形成MHR-DC网络模型.MHR-DC网络在基本不增加数据分组汇聚全程转发跳数的前提下,通过同跳节点代传以保证所有源生负载的高可靠传输、通过抑制数据分组的重复传送程度以提高网络能量效率、通过避开转发负载重的节点区域以达到负载均衡,优化网络综合性能指标,并增强网络时延最小的潜在优势.理论及仿真分析表明,该机制能保证网络数据传输的高可靠性和能量有效性以及优越的网络综合性能.     

基于多蚁群算法的无线传感器网络路由的跨层设计

针对事件驱动型无线传感器网络对数据传输的强实时性和高可靠性的要求,将统计获得的节点接入效率和负载队列长度等MAC层状态信息作为路由度量参数。考虑到蚂蚁网络算法在重负荷网络中存在传输延迟大、聚合速度慢等缺陷,提出了一种基于多蚁群算法的负载感知和高效接入的跨层路由协议,该协议把节点的单跳延迟、负载及带宽接入效率等参数作为路径的启发值进行路由优化。仿真结果表明,基于多蚁群算法的路由协议能够保证数据传输的实时性,能够实现无线传感器网络的拥塞控制及负载平衡。     

一种基于数据流跟踪的无线传感网能量模型及网络优化

提出了一种基于数据流跟踪的能量模型,通过跟踪数据流在网络中的整个过程来计算全网的能量消耗,是一种不受网络结构限制的普遍适用的能量模型;在此基础上.建立了基于能耗的网络优化模型,针对链式和簇式结构进行了拓扑、功率和路由方面的优化设计,仿真结果证明了理论分析的正确性.     

不确定数据上两种查询的分布式聚集算法

不确定数据查询技术在军事、金融、电信等领域中起到了越来越重要的作用.不确定性数据在传感器网络、分布式Web Server及P2P系统等分布式系统中广泛存在.从这些系统中收集所有数据进行集中式查询将带来巨大的通信开销、时间延迟和存储代价.同时,由于不确定数据的特点,大多数集中式不确定查询算法在分布式环境下并不适用.给出不确定数据的最大值和Top-k聚集查询定义,并分别提出了基于过滤策略的分布式聚集算法.算法根据给出的3个过滤策略,利用数据的分布区间和概率进行筛选概率上限的计算,尽可能将不影响查询结果的数据抛弃.同时,算法以相对较小的代价归并保存并传输了计算最终查询结果所需要的不可丢弃数据.实验结果表明,在各类系统和数据条件下,过滤算法都能够正确地得到查询结果并显著降低系统的数据通信开销.     

An analytical model for information retrieval in wireless sensor networks using enhanced APTEEN protocol

Wireless sensor networks are a new class of ad hoc networks that will find increasing deployment in coming years, as they enable reliable monitoring and analysis of unfamiliar and untested environments. The advances in technology have made it possible to have extremely small, low powered sensor devices equipped with programmable computing, multiple parameter sensing, and wireless communication capability. Because of their inherent limitations, the protocols designed for such sensor networks must efficiently use both limited bandwidth and battery energy. We develop an M/G/1 model to analytically determine the delay incurred in handling various types of queries using our enhanced APTEEN (Adaptive Periodic Threshold-sensitive Energy Efficient sensor Network protocol) protocol. Our protocol uses an enhanced TDMA schedule to efficiently incorporate query handling, with a queuing mechanism for heavy loads. It also provides the additional flexibility of querying the network through any node in the network. To verify our analytical results, we have simulated a temperature sensing application with a Poisson arrival rate for queries on the network simulator ns-2. As the simulation and analytical results match perfectly well, this can be said to be the first step towards analytically determining the delay characteristics of a wireless sensor network.     

Object extraction scheme and protocol for energy efficient image communication over wireless sensor networks

To date, wireless sensor networks lack the most powerful human sense – vision. This is largely due to two main problems: (1) available wireless sensor nodes lack the processing capability and energy resource required to efficiently process and communicate large volume of image data and (2) the available protocols do not provide the queue control and error detection capabilities required to reduce packet error rate and retransmissions to a level suitable for wireless sensor networks. This paper presents an innovative architecture for object extraction and a robust application-layer protocol for energy efficient image communication over wireless sensor networks. The protocol incorporates packet queue control mechanism with built-in CRC to reduce packet error rate and thereby increase data throughput. Unlike other image transmission protocols, the proposed protocol offers flexibility to adjust the image packet size based on link conditions. The proposed processing architecture achieves high speed object extraction with minimum hardware requirement and low power consumption. The system was successfully designed and implemented on FPGA. Experimental results obtained from a network of sensor nodes utilizing the proposed architecture and the application-layer protocol reveal that this novel approach is suitable for effectively communicating multimedia data over wireless sensor networks.     

A dynamic programming approach: Improving the performance of wireless networks

Traditional wireless networks focus on transparent data transmission where the data are processed at either the source or destination nodes. In contrast, the proposed approach aims at distributing data processing among the nodes in the network thus providing a higher processing capability than a single device. Moreover, energy consumption is balanced in the proposed scheme since the energy intensive processing will be distributed among the nodes. The performance of a wireless network is dependent on a number of factors including the available energy, energy–efficiency, data processing delay, transmission delay, routing decisions, security architecture etc. Typical existing distributed processing schemes have a fixed node or node type assigned to the processing at the design phase, for example a cluster head in wireless sensor networks aggregating the data. In contrast, the proposed approach aims to virtualize the processing, energy, and communication resources of the entire heterogeneous network and dynamically distribute processing steps along the communication path while optimizing performance. Moreover, the security of the communication is considered an important factor in the decision to either process or forward the data. Overall, the proposed scheme creates a wireless “computing cloud” where the processing tasks are dynamically assigned to the nodes using the Dynamic Programming (DP) methodology. The processing and transmission decisions are analytically derived from network models in order to optimize the utilization of the network resources including: available energy, processing capacity, security overhead, bandwidth etc. The proposed DP-based scheme is mathematically derived thus guaranteeing performance. Moreover, the scheme is verified through network simulations.     

基于外层空间的无线传感器网络组播路由协议研究*

研究航天器部署在火星表面的无线传感器节点,首次提出了外层空间无线传感器网络(outer space wireless sensor network,OSWSN)的概念,指出该网络的节点以自组织方式组网。基于已有的地面无线传感器网络经典组播路由协议,结合无线自组织网络组播协议建树思想,设计应用于外层空间无线传感器网络的OSWSNMP（OSWSN multicast protocol）。与已有的MAODV组播路由协议以及应用于地面无线传感器网络的EMRS组播路由协议进行比较,在NS2上搭建OSWSNMP仿真环     

Energy-saving models for wireless sensor networks

Nowadays, wireless sensor networks are being used for a fast-growing number of different application fields (e.g., habitat monitoring, highway traffic monitoring, remote surveillance). Monitoring (i.e., querying) the sensor network entails the frequent acquisition of measurements from all sensors. Since sensor data acquisition and communication are the main sources of power consumption and sensors are battery-powered, an important issue in this context is energy saving during data collection. Hence, the challenge is to extend sensor lifetime by reducing communication cost and computation energy. This paper thoroughly describes the complete design, implementation and validation of the SeReNe framework. Given historical sensor readings, SeReNe discovers energy-saving models to efficiently acquire sensor network data. SeReNe exploits different clustering algorithms to discover spatial and temporal correlations which allow the identification of sets of correlated sensors and sensor data streams. Given clusters of correlated sensors, a subset of representative sensors is selected. Rather than directly querying all network nodes, only the representative sensors are queried by reducing the communication, computation and power costs. Experiments performed on both a real sensor network deployed at the Politecnico di Torino labs and a publicly available dataset from Intel Berkeley Research lab demonstrate the adaptability and the effectiveness of the SeReNe framework in providing energy-saving sensor network models.