A semantic-based architecture for sensor networks

With rapid development of sensor networks technology, it becomes feasible to deploy multiple sensor networks in relevant area to collect interested information. Sensor nodes that are co-located but belong to different sensor networks may not be able to collaborate properly to gain the capacity or performance. In this paper we propose a semantic-based sensor networks architecture that enables inter-networking of sensor networks. In this Semantic Sensor Net (Ssn), a semantic tag is attached to the sensory data so that the sensor networks are able to exchange information and work collaboratively. The process of semantic creation and maintenance is described. We also introduce the concept of InterSensorNet. This infrastructure enables efficient information exchange and information extraction among multiple sensor networks.     

Communication paradigms for sensor networks

When compared with now classical MANETs, sensor networks have different characteristics, and present different design and engineering challenges. One of the main aspects of sensor networks is that the solutions tend to be very application-specific. For this reason, a layered view like the one used in OSI imposes a large penalty, and implementations more geared toward the particular are desirable. This survey presents the three main paradigms for communication in ad hoc networks and discusses their applicability for routing, querying, and discovery. We conclude that the node-centric approach, although the oldest and best understood, is not the most appropriate for large-size low-energy application-specific sensor networks.     

An autonomic-oriented architecture for wireless sensor networks

Autonomic communication is a new paradigm to enable network self-configuration, self-organization, self-healing, and autonomic behaviour. Emerging networks need this autonomic behaviour in order to ensure mainly quality of service, resilience and reliability of the network which is highly necessary for a long term service operation. Typical environments where such a deployment is extremely important come from wireless sensor networks. Indeed, sensor networks are strongly distributed and need for a self-organized and self-manageable architecture to provide a reliable service support. To come up with these properties, this paper introduces a new autonomic-oriented architecture (AoA) for wireless sensor networks.     

Secure K-Nearest neighbor queries in two-tiered mobile wireless sensor networks

Tiered Mobile Wireless Sensor Network(TMWSN) is a new paradigm introduced by mobile edge computing. Now it has received wide attention because of its high scalability, robustness, deployment flexibility, and it has a wide range of application scenarios. In TMWSNs, the storage nodes are the key nodes of the network and are more easily captured and utilized by attackers. Once the storage nodes are captured by the attackers, the data stored on them will be exposed. Moreover, the query process and results will not be trusted any more. This paper mainly studies the secure KNN query technology in TMWSNs, and we propose a secure KNN query algorithm named the Basic Algorithm For Secure KNN Query(BAFSKQ) first, which can protect privacy and verify the integrity of query results. However, this algorithm has a large communication overhead in most cases. In order to solve this problem, we propose an improved algorithm named the Secure KNN Query Algorithm Based on MR-Tree(SEKQAM). The MR-Trees are used to find the K-nearest locations and help to generate a verification set to process the verification of query results. It can be proved that our algorithms can effectively guarantee the privacy of the data stored on the storage nodes and the integrity of the query results. Our experimental results also show that after introducing the MR-Trees in KNN queries on TMWSNs, the communication overhead has an effective reduction compared to BAFSKQ.     

Geo-casting of queries combined with coverage area reporting for wireless sensor networks

In order to efficiently deal with queries or other location dependent information, it is key that the wireless sensor network informs gateways what geographical area is serviced by which gateway. The gateways are then able to e.g. efficiently route queries which are only valid in particular regions of the deployment. The proposed algorithms combine coverage area reporting and geographical routing of queries which are injected by gateways. The combined solution is evaluated in terms of computational complexity and performance compared with existing geocasting protocols.     

A hierarchical adaptive spatio-temporal data compression scheme for wireless sensor networks

Wireless Networks - How to reduce the number of transmissions or prolong the lifetime of wireless sensor networks significantly has become a great challenge. Based on the spatio-temporal...     

MANNA: a management architecture for wireless sensor networks

Wireless sensor networks (WSNs) are becoming an increasingly important technology that will be used in a variety of applications such as environmental monitoring, infrastructure management, public safety, medical, home and office security, transportation, and military. WSNs will also play a key role in pervasive computing where computing devices and people are connected to the Internet. Until now, WSNs and their applications have been developed without considering a management solution. This is a critical problem since networks comprising tens of thousands of nodes are expected to be used in some of the applications above. This article proposes the MANNA management architecture for WSNs. In particular, it presents the functional, information, and physical management architectures that take into account specific characteristics of this type of network. Some of them are restrict physical resources such as energy and computing power, frequent reconfiguration and adaptation, and faults caused by nodes unavailable. The MANNA architecture considers three management dimensions: functional areas, management levels, and WSN functionalities. These dimensions are specified to the management of a WSN and are the basis for a list of management functions. The article also proposes WSN models to guide the management activities and the use of correlation in the WSN management. This is a first step into a largely unexplored research area.     

Real-time multimedia processing in video sensor networks

Video sensor networks (VSNs) has become the recent research focus due to the rich information it provides to address various data-hungry applications. However, VSN implementations face stringent constraints of limited communication bandwidth, processing capability, and power supply. In-network processing has been proposed as efficient means to address these problems. The key component of in-network processing, task mapping and scheduling problem, is investigated in this paper. Although task mapping and scheduling in wired networks of processors has been extensively studied, their application to VSNs remains largely unexplored. Existing algorithms cannot be directly implemented in VSNs due to limited resource availability and shared wireless communication medium. In this work, an application-independent task mapping and scheduling solution in multi-hop VSNs is presented that provides real-time guarantees to process video feeds. The processed data is smaller in volume which further releases the burden on the end-to-end communication. Using a novel multi-hop channel model and a communication scheduling algorithm, computation tasks and associated communication events are scheduled simultaneously with a dynamic critical-path scheduling algorithm. Dynamic voltage scaling (DVS) mechanism is implemented to further optimize energy consumption. According to the simulation results, the proposed solution outperforms existing mechanisms in terms of guaranteeing application deadlines with minimum energy consumption.     

Power, spatio-temporal bandwidth, and distortion in large sensor networks

For a class of sensor networks, the task is to monitor an underlying physical phenomenon over space and time through an imperfect observation process. The sensors can communicate back to a central data collector over a noisy channel. The key parameters in such a setting are the fidelity (or distortion) at which the underlying physical phenomenon can be estimated by the data collector, and the cost of operating the sensor network. This is a network joint source-channel communication problem, involving both compression and communication. It is well known that these two tasks may not be addressed separately without sacrificing optimality, and the optimal performance is generally unknown. This paper presents a lower bound on the best achievable end-to-end distortion as a function of the number of sensors, their total transmit power, the number of degrees of freedom of the underlying source process, and the spatio-temporal communication bandwidth. Particular coding schemes are studied, and it is shown that in some cases, the lower bound is tight in a scaling-law sense. By contrast, it is shown that the standard practice of separating source from channel coding may incur an exponential penalty in terms of communication resources, as a function of the number of sensors. Hence, such code designs effectively prevent scalability. Finally, it is outlined how the results extend to cases involving missing synchronization and channel fading.     

An ultrawideband system architecture for tag based wireless sensor networks

With the latest improvements in device size, power consumption, and communications, sensor networks are becoming increasingly more popular. There has also been a great increase in the popularity of commercial applications based on ultrawideband (UWB). Impulse radio (IR) based UWB technology utilizes noise-like signal, has potentially low complexity and low cost, is resistant to severe multipath, and has very good time domain resolution allowing for location and tracking applications. In this paper, the architecture and performance of a noncoherent low complexity UWB impulse radio based transceiver designed for low data rate, low cost sensor network applications is presented. The UWB-IR transmitter is based on a delay locked loop (DLL) and UWB monocycle pulse generator. The UWB-IR receiver utilises a noncoherent, energy detection based approach, which makes it largely independent of the shape of the transmit waveform and robust to multipath channels. The test circuits are designed for 0.35 /spl mu/m SiGe BiCMOS technology. This paper presents system simulations results as well as the performance of key functional blocks of the designed UWB application specific integrated circuit (ASIC) transceiver architecture. The simulated power consumption of UWB-IR transceiver circuits is 136 mW with 100% duty cycle with a 3.3 V power supply.     

QoSMOS: cross-layer QoS architecture for wireless multimedia sensor networks

Wireless multimedia sensor networks (WMSNs), having inherent features and limited resources, require new quality of service (QoS) protocols for real-time and multimedia applications. In this paper, we present a cross-layer QoS architecture (QoSMOS), that unifies network and link layers into a single communication module for QoS provisioning. Based on QoSMOS architecture, we developed an example reference cross-layer protocol, named cross-layer communication protocol (XLCP), enabling scalable service differentiation in WMSNs. Comprehensive analysis of simulation results indicate that the proposed architecture successfully differentiates service classes in terms of soft delay, reliability and throughput domains. A comparative analysis of XLCP and its counterparts is also given to show the superiority of the cross-layer protocol.     

Dynamic power management in new architecture of wireless sensor networks

Dynamic power management (DPM) technology has been widely used in sensor networks. Though many specific technical challenges remain and deserve much further study, the primary factor currently limiting progress in sensor networks is not these challenges but is instead the lack of an overall sensor network architecture. In this paper, we first develop a new architecture of sensor networks. Then we modify the sleep state policy developed by Sinha and Chandrakasan in (IEEE Design Test Comput. 2001; 18 (2):62–74) and deduce that a new threshold satisfies the sleep‐state transition policy. Under this new architecture, nodes in deeper sleep states consume lower energy while asleep, but require longer delays and higher latency costs to awaken. Implementing DPM with considering the battery status and probability of event generation will reduce the energy consumption and prolong the whole lifetime of the sensor networks. We also propose a new energy‐efficient DPM, which is a modified sleep state policy and combined with optimal geographical density control (OGDC) (Wireless Ad Hoc Sensor Networks 2005; 1 (1–2):89–123) to keep a minimal number of sensor nodes in the active mode in wireless sensor networks. Implementing dynamic power management with considering the battery status, probability of event generation and OGDC will reduce the energy consumption and prolong the whole lifetime of the sensor networks. Copyright © 2008 John Wiley & Sons, Ltd.     

Accurate compressive data gathering in wireless sensor networks using weighted spatio-temporal compressive sensing

The high number of transmissions in sensor nodes having a limited amount of energy leads to a drastic decrease in the lifetime of wireless sensor networks. For dense sensor networks, the provided data potentially have spatial and temporal correlations. The correlations between the data of the nodes make it possible to utilize compressive sensing theory during the data gathering phase; however, applying this technique leads to some errors during the reconstruction phase. In this paper, a method based on weighted spatial-temporal compressive sensing is proposed to improve the accuracy of the reconstructed data. Simulation results confirm that the reconstruction error of the proposed method is approximately 16 times less than the closest compared method. It should be noted that due to applying weighted spatial-temporal compressive sensing, some extra transmissions are posed to the network. However, considering both lifetime and accuracy factors as a compound metric, the proposed method yields a 12% improvement compared to the closest method in the literature.     

IDRA: A flexible system architecture for next generation wireless sensor networks

Wireless sensor networks consist of embedded devices (sensor nodes), equipped with a low-power radio. They are used for many applications: from wireless building automation to e-health applications. However, due to the limited capabilities of sensor nodes, designing network protocols for these constrained devices is currently very challenging. Therefore, this paper presents the IDRA platform: an information driven architecture designed to support next-generation applications on resource constrained networked objects. IDRA supports simple but useful optimizations at an architectural level. These include support for cross-protocol interactions, energy efficiency optimizations, QoS optimizations (packet priorities, dynamic protocol selection), mobility support and heterogeneous network support. The paper shows how the development of protocols is improved by using an architecture which delegates specific tasks to a central system, decreasing the memory requirements of associated network protocols. A thorough experimental performance analysis demonstrates that IDRA is much more scalable in terms of memory requirements, energy requirements and processing overhead than traditional system architectures. Finally, the paper discusses how the optimizations presented in this paper can be used for the clean-slate design of architectures for other wireless or wired network types.     

Mobile-agent-based collaborative signal and information processing in sensor networks

In this paper, we develop an energy-efficient, fault-tolerant approach for collaborative signal and information processing (CSIP) among multiple sensor nodes using a mobile-agent-based computing model. In this model, instead of each sensor node sending local information to a processing center for integration, as is typical in client/server-based computing, the integration code is moved to the sensor nodes through mobile agents. The energy efficiency objective and the fault tolerance objective always conflict with each other and present unique challenge to the design of CSIP algorithms. In general, energy-efficient approaches try to limit the redundancy in the algorithm so that minimum amount of energy is required for fulfilling a certain task. On the other hand, redundancy is needed for providing fault tolerance since sensors might be faulty, malfunctioning, or even malicious. A balance has to be struck between these two objectives. We discuss the potential of mobile-agent-based collaborative processing in providing progressive accuracy while maintaining certain degree of fault tolerance. We evaluate its performance compared to the client/server-based collaboration from perspectives of energy consumption and execution time through both simulation and analytical study. Finally, we take collaborative target classification as an application example to show the effectiveness of the proposed approach.     

Data processing and communication strategies for lifetime optimization in wireless sensor networks

In this paper we introduced a novel Linear Programming framework to model sensor network lifetime when data reduction through compression is utilized. Comparative analysis of three data compression and forwarding strategies show that neither data compression nor flow balancing can achieve the maximal possible sensor network lifetime when optimized independently. The comparisons reveal that jointly optimizing data compression and load balancing results in up to an order of magnitude longer network lifetimes than non-optimized data compression and load balancing.     

传感器网络数据处理中基于隐私向量的隐私保护机制

针对传感器网络数据处理中的隐私保护需求,提出了新的分布式机制。构造了隐私向量,并设计了低能耗的隐私向量生成方法及使用方法,从而可有效实现求和、求最值及压缩等各类处理中的数据隐私保护。提出了种子分发算法,保证了隐私向量的安全动态生成。理论分析和仿真实验表明,与已有同类机制相比,新机制不仅能更好地抵御节点俘获攻击,具有更高的隐私保护有效性,且更为能量有效。     

Fault tolerant queries in computer networks

In computer networks with decentralized control, it is necessary to provide a distributed query mechanism, whereby a node can dynamically discover the location of a remote resource. The authors propose a query mechanism based on flooding with feedback, which uses no more than two messages over any link. They examine the fault tolerant aspects of this distributed query mechanism, operating in a network where links and nodes may fail and show that, under certain conditions, the resource is indeed found. They then construct enhancements to this mechanism, where the conditions under which the resource is found are substantially relaxed, at the cost of some increase in message complexity     

ProTru: a provenance‐based trust architecture for wireless sensor networks

Trust is an important component of wireless sensor networks for believability of the produced data, and trust history is a crucial asset in deciding trust of the data. In this paper, we show how provenance can be used for registering previous trust records and other information such as node type, data type, and node location. Our aim is to design a distributed trust‐enhancing architecture using only local provenance during sensor fusion with a low communication overhead. Our network is cognitive in the sense that our system reacts automatically upon detecting low trust. Copyright © 2016 John Wiley & Sons, Ltd.