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A Distributed Publish/Subscribe System for Large Scale Sensor Networks
Abstract
As sensor and wireless network technologies are developed, it is expected that we will be able to gather lots of sensor data from various sensors on globe. Combining/ aggregating these sensor data, many useful applications could be developed. However, it is difficult to aggregate sensor data and secure scalability, because in some case too much sensor data concentrate on some specific nodes. Then, we add data processing components onto content-based networks, considering division and reassign of processing components. Content-based networks provide publish/ subscribe system in distributed environment and appropriate for notifications and alerts. If content-based networks process published data and create meaningful information, this system enhance the application fields in ubiquitous sensing environment. In this paper, we model sensor data calculation process and describe how to add data processing components onto content-based networks. On the contrary, data processing components causes concentrations of sensor data. We also describe load distribution mechanism of these components. Performance evaluations of our implementation shows that load distribution mechanism works well, and proposed system secure the scalability by adding data components.
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In recent years, sensors have become smaller, more affordable, and widely used. Also, Internet spreads all over the globe, and made possible transfer large data instantly. Thereby, large scale weather sensor networks have been constructible. In this kind of sensor network, we need to consider load balancing, network redundancy, and reliability of sensor data. Using P2P technology is one of the solutions for load balancing and network redundancy. Fault detection is a method for calculating reliability of sensor data. We propose a system that can calculate reliability of sensor data. This system can install method of fault detection by plug-in. It can install and update not only existing method but also new method. In other words, this system is a sustainable fault detection system. In these days, pinpoint heavy rain is occurring frequently. In this paper, we validate a fault detection system at a pinpoint heavy rain. We consider a validation, and improve a plug-in that can be useful at a pinpoint heavy rain. We install the improved plug-in to system, and experiment it using real pinpoint heavy rain data. The result shows that our system can detect 100% of data fault at pinpoint heavy rain which occurred in August 29th, 2008.
Development of sensor technology enables us to use lots of and detailed information. Then, it is difficult to deal with the vast number of information generated by sensors by client server model. In order to deal with data generated by sensors, we build a new information infrastructure on overlay network. In this paper, we propose an overlay network system considering time and location on which data is generated. For efficient store and search, we create 3-dimensional space by time and location. Our proposed method supports range search and periodic search, using gradual aggregation on time dimension. In addition, to estimate our proposed overlay network, we implement simulator with Java on TCP/IP network
Borealis is a second-generation distributed stream pro-cessing engine that is being developed at Brandeis Uni-versity, Brown University, and MIT. Borealis inherits core stream processing functionality from Aurora [14] and distribution functionality from Medusa [51]. Bo-realis modifies and extends both systems in non-trivial and critical ways to provide advanced capabilities that are commonly required by newly-emerging stream pro-cessing applications. In this paper, we outline the basic design and function-ality of Borealis. Through sample real-world applica-tions, we motivate the need for dynamically revising query results and modifying query specifications. We then describe how Borealis addresses these challenges through an innovative set of features, including revi-sion records, time travel, and control lines. Finally, we present a highly flexible and scalable QoS-based opti-mization model that operates across server and sensor networks and a new fault-tolerance model with flexible consistency-availability trade-offs. 1 Introduction
Advances in data acquisition and sensor technologies are leading towards the development of "high fan-in" architectures: widely distributed systems whose edges consist of numerous receptors such as sensor networks, RFID readers, or probes, and whose interior nodes are traditional host computers organized using the principles of cascading streams and successive aggregation. Examples include RFID-enabled supply chain management, large- scale environmental monitoring, and various types of network and computing infrastructure monitoring. In this paper, we identify the key characteristics and data management challenges presented by high fan-in systems, and argue for a uniform, query-based approach towards addressing them. We then present our initial design concepts behind HiFi, the system we are building to embody these ideas, and describe a proof-of-concept prototype.
This document summarizes the research conducted in two inte rrelated projects. The Aurora project being implemented at Brown and Brandeis under the direction of U ˘ gur Cetintemel, Mitch Cherniack, Michael Stonebraker and Stan Zdonik strives to build a single-site h igh performance stream processing engine. It has an innovative collection of operators, workflow orien tation, and strives to maximize quality of service for connecting applications. A further goal of Auro ra is to extend this engine to a distributed environment in which multiple machines closely co-operatein achieving high quality of service. In contrast, the Medusa project being investigated at M.I.T. under the direction of Hari Balakrish- nan and Michael Stonebraker is providing networking infras tructure for Aurora operations. In addition, Medusa is stressing distributed environments where the var ious machines belong to different organiza- tions. In this case, there can be no common goal, and much loos er coupling is needed. Medusa is work- ing on an innovative agoric infrastructure in which variousparticipants can co-operate in distributed streaming operations. Finally, some have questioned whether specialized stream p rocessing software is necessary. They speculate that conventional data base systems can adequate ly deal with the needs of stream-oriented applications. In order to answer this question one way or the other, both groups are working on a stream- oriented benchmark, called the Linear Road benchmark, which we intend to run on both specialized and conventional system infrastructure.
A key problem in current sensor network technology is the heterogeneity of the available software and hardware platforms which makes deployment and application development a tedious and time consuming task. To minimize the unnecessary and repetitive implementation of identical functionalities for different platforms, we present our Global Sensor Networks (GSN) middleware which supports the flexible integration and discovery of sensor networks and sensor data, enables fast deployment and addition of new platforms, provides distributed querying, filtering, and combination of sensor data, and supports the dynamic adaption of the system configuration during operation. In this demonstration, we specifically focus on the deployment aspects and allow users to dynamically reconfigure the running system, to add new sensor networks on the fly, and to monitor the effects of the changes via a graphical interface.
The availability of cheap and smart wireless sensing devices provides unprecedented possibilities to monitor the physical world. On the technical side these devices introduce several original research problems, many of them related to the integration of the rampant technology proposals. Global Sensor Network (GSN) is a platform which provides a scalable infrastructure for integrating heterogeneous sensor network technologies using a small set of powerful abstractions. GSN supports the integration and discovery of sensor networks and sensor data, provides distributed querying, filtering, and combination of sensor data, and supports the dynamic adaption of the system configuration during operation through a declarative XML-based language
To leverage location-related information is useful to get an in-depth perspective on environmental circumstances, traffic situations and/or other problems. To handle the large number of information and queries communication devices issue, some scalable mechanism must be required. In this paper, we propose a peer-to-peer network system called "Mill" which can efficiently handle information related to the geographical location. To simplify the management of the location related information, we convert two dimensional coordinates into one dimensional circumference. Using this technique, Mill can search information by O(log N). Some DHT networks achieve the same performance. However, DHTs support only exact match lookups. The exact match is not suitable for searching information of a particular region. Mill provides an effective region search, by which users can search flexibly location-related information from small regions to large regions.
We discuss about the IrisNet (Internet-scale resource-intensive sensor network services) project at Intel Research, we design an architecture and build a system that enable easy deployment of such wide-area sensing services. We aim to provide the missing software components for realizing a worldwide sensor Web. Wide-area architectures for pervasive sensing enable a new generation of powerful distributed sensing services. A worldwide sensor Web, in which users can query, as a single unit, vast quantities of data from thousands or even millions of widely distributed, heterogeneous sensors. Internet-connected PCs that source sensor feeds and cooperate to answer users' queries will form the global sensor Web's backbone. Developers of wide-area sensing services (service authors) deploy the services on this distributed infrastructure.
A set of services and interface primitives to be offered to an application programmer of an ad hoc wireless sensor and actuator network (AWSAN) is described. As the definition of sockets has made the use of communication services in the Internet independent of the underlying protocol stack, communication medium and even operating system, the proposed application interface, called the “sensor network services platform” (SNSP), identifies an abstraction that is offered to any sensor network application and supported by any sensor network platform. The SNSP builds on the query/command paradigm already used in several sensor network implementations and further adds time synchronization, location and naming services that support the communication and coordination among application components.
Wireless Sensor Networks (WSNs) have become a new information collection and monitoring solution for a variety of applications. Faults occurring to sensor nodes are common due to the sensor device itself and the harsh environment where the sensor nodes are deployed. In order to ensure the network quality of service it is necessary for the WSN to be able to detect the faults and take actions to avoid further degradation of the service. The goal of this paper is to locate the faulty sensors in the wireless sensor networks. We propose and evaluate a localized fault detection algorithm to identify the faulty sensors. The implementation complexity of the algorithm is low and the probability of correct diagnosis is very high even in the existence of large fault sets. Simulation results show the algorithm can clearly identify the faulty sensors with high accuracy.
Abstract Sensor devices and embedded processors are becoming ubiquitous Their limited resources (CPU, memory and/or communication band - width and power) pose some interesting chal - lenges We need both powerful and concise "languages" to represent the important fea - tures of the data, which can (a) adapt and handle arbitrary periodic components, includ - ing bursts, and (b) require little memory and a single pass over the data We propose AWSOM (Arbitrary Window Stream mOdeling Method), which allows sen - sors in remote or hostile environments to e - ciently and e ectively discover interesting pat - terns and trends This can be done automat - ically , i e , with no user intervention and ex - pert tuning before or during data gathering Our algorithms require limited resources and can thus be incorporated in sensors, possi - bly alongside a distributed query processing
The emergence of computationally-enabled sensors and the applica-tions that use sensor data introduces the need for a software infrastruc-ture designed specifically to enable the rapid development and deploy-ment of applications that draw upon data from multiple, heterogeneous sensor networks. We present the Hourglass infrastructure, which ad-dresses this need. Hourglass is an Internet-based infrastructure for connecting a wide range of sensors, services, and applications in a robust fashion. In Hourglass, a stream of data elements is routed to one or more appli-cations. These data elements are generated from sensors inside of sen-sor networks whose internals can be entirely hidden from participants in the Hourglass system. The Hourglass infrastructure consists of an overlay network of well-connected dedicated machines that provides service registration, discovery, and routing of data streams from sen-sors to client applications. In addition, Hourglass supports a set of in-network services such as filtering, aggregation, compression, and buffering stream data between source and destination. Hourglass also allows third party services to be deployed and used in the network. In this paper, we present the Hourglass architecture and describe our test-bed and implementation. We demonstrate how our design maintains streaming data flows in the face of disconnection, allows discovery of and access to data from sensors, supports participants of widely varying capabilities (servers to PDAs), takes advantage of well-provisioned, well-connected machines, and provides separate efficient communication paths for short-lived control messages and long-lived stream-oriented data.
Due to the global spread of the Internet and the rapidly diminishing price of wireless sensors, a large number of heterogeneous
sensor networks have been developed and interconnected around the globe for the sharing of sensing data on a global scale.
Such data greatly affect our daily lives, such as environmental issues and business development. A scalable decentralized
system that provides multiple-attribute search is a key mechanism for sharing sensing data on a global scale. In this chapter,
current sensor networks and distributed data management approaches are introduced. In particular, we discuss an implementation
of distributed mechanisms and propose a geographical-based overlay network for managing ubiquitous sensors.
Keywordslarge scale sensor networks-distributed data management
This paper introduces monitoring applications, which we will show differ substantially from conventional business data processing. The fact that a software system must process and react to continual inputs from many sources (e.g., sensors) rather than from human operators requires one to rethink the fundamental architecture of a DBMS for this application area. In this paper, we present Aurora, a new DBMS that is currently under construction at Brandeis University, Brown University, and M.I.T. We describe the basic system architecture, a stream-oriented set of operators, optimization tactics, and support for real- time operation.
As more and more physical information becomes available, a critical problem is enabling the simple and efficient exchange of this data. We present our design for a simple RESTful web service called the Simple Measuring and Actuation Profile (sMAP) which allows instruments and other producers of physical information to directly publish their data. In our design study, we consider what information should be represented, and how it fits into the RESTful paradigm. To evaluate sMAP, we implement a large number of data sources using this profile, and consider how easy it is to use to build new applications. We also design and evaluate a set of adaptations made at each layer of the protocol stack which allow sMAP to run on constrained devices.
The existing tools for software updates in workstations cannot be used with the severely resource constrained sensor nodes. In this article, we survey the software update techniques based on a conceptual model in WSNs. Three components of this model that we study are the execution environment at the sensor nodes, the software distribution protocol in the network and optimization of transmitted updates. Abstract Software management is a critical task in the system administration of enterprise scale net- works. Enterprise scale networks that have traditionally comprised of large clusters of worksta- tions are expanding to include low power ad-hoc wireless sensor networks (WSN). The existing tools for software updates in workstations cannot be used with the severely resource constrained sensor nodes. In this article, we survey the software update techniques in WSNs. We base our discussion around a conceptual model for the software update tools in WSNs. Three components of this model that we study are the execution environment at the sensor nodes, the software distribution protocol in the network and optimization of transmitted updates. We present the design space of each component and discuss in-depth the trade os that need to be considered in making a particular design choice. The discussion is interspersed with references to deployed systems that highlight the design choices.
This paper proposes a routing scheme for content-based networking. A content-based network is a communication network that features a new advanced communication model where messages are not given explicit destination addresses, and where the destinations of a message are determined by matching the content of the message against selection predicates declared by nodes. Routing in a content-based network amounts to propagating predicates and the necessary topological information in order to maintain loop-free and possibly minimal forwarding paths for messages. The routing scheme we propose uses a combination of a traditional broadcast protocol and a content-based routing protocol. We present the combined scheme and its requirements over the broadcast protocol. We then detail the content-based routing protocol, highlighting a set of optimization heuristics. We also present the results of our evaluation, showing that this routing scheme is effective and scalable.
This paper presents an algorithm for content-based forwarding, an essential function in content-based networking. Unlike in traditional address-based unicast or multicast networks, where messages are given explicit destination addresses, the movement of messages through a content-based network is driven by predicates applied to the content of the messages. Forwarding in such a network amounts to evaluating the predicates stored in a router's forwarding table in order to decide to which neighbor routers the message should be sent. We are interested in finding a forwarding algorithm that can make this decision as quickly as possible in situations where there are numerous, complex predicates and high volumes of messages. We present such an algorithm and give the results of studies evaluating its performance.
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