References. K. Sohraby, D. Minoli, and T. Znati. Wireless Sensor Networks: Technology, Protocols, and

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1 Middleware

2 References K. Sohraby, D. Minoli, and T. Znati. Wireless Sensor Networks: Technology, Protocols, and Applications. John Wiley & Sons, (Chapter t 8) Y. Yu, B. Krishnamachari, and V. K. Prasanna. Issues in Designing Middleware for Wireless Sensor Networks. IEEE Network, Vol. 18, Issue 1, pp , January/February

3 Introduction Usually, there is a gap between the applications and network protocols in wireless networks Adaptation functions are needed to satisfy the requirements of special features of WSNs and diversity i of potential applications Middleware A software level between the applications and the underlying operating environment (OS, protocols, etc.) Needs to provide A standardized system services to applications A runtime environment that can support and coordinate multiple applications Mechanisms to achieve adaptive and efficient utilization of system resources 3

4 Challenges 4 Traditional (distributed) ib t d) middleware are not suitable for WSNs, because They generally are heavyweight ht in terms of resource requirements The operating modes of WSNs are different than traditional networks The key problem in WSN is the energy conservation. For it: Efficient mechanisms are needed to selectively activate sleeping nodes The activated nodes need to cooperate with each other for the required signal processing tasks Certain QoS requirements must be met

5 Localized algorithms Design principles p Distributed algorithms that achieve a global goal by local (neighbor) coordination Adaptive fidelity algorithms Trade the quality of the result against resource usage (key element for resource efficiency) Data-centric communication 5 Addressing node by focusing on the data produced on the node Application knowledge For data caching and aggregation

6 A cluster-based architecture 6 A p pl ic a t io n s Application code, specification, QoS requirements, adaptation policies i Application results, resource usage, and QoS statistics Resource management layer Cluster layer Resource description Cluster information QoS interpreter Resource manager Cost models Resource allocation and adaptation Cluster forming and control protocol Virtu ual Machine Data accessibility, node capability, network connectivity i Sensor state control, knob settings, code allocation, cluster control messages Sensor Network

7 A cluster-based architecture 2 The key is to abstract t common properties of applications and map them to the underlying (network) architecture Three-tiered 7 A virtual machine provides an abstraction of the middleware Cluster layer Resource management layer Applications Sensor network

8 Approaches Middleware architecture Dynamic network configuration Databases and queries Data fusion Event detection Monitoring System platforms Data-related functions Data dissemination Data compression Data storage 8

9 MiLAN[1] [] Middleware Linking Applications and Networks Two classes of applications Data-driven Collect and analyze data State-basedt Application requirements may change based on receive data 9

10 IrisNet[2] 10 Internet-Scale Resource-Intensive Sensor Network Services Extends the traditional WSNs to a worldwide sensor web Can integrate a wide range of sensor data, from a high-bit rate to a low-bit rate Two tiers: Sensing agents (SAs) Implement generic data acquisition interface to access sensors Organizing agents (OAs) Implement a distributed database to store service-specific data that SAs produce; uses XML S s p oduce; uses Does not address resource constraints

11 AMF[3] Adaptive Middleware Framework Exploits resource and application QoS trade-offs and predictability of sensor readings to reduce energy consumption Two components Sensor side Sensor state management Precision driven adaptation Server side 11 Maintains a list of active sensors and a list of historic values for each sensor

12 DSWare[4] Data Service Middleware Resides between the application and network layers Integrates t various real-time data services Provides a database-like abstraction to applications Several components Data storage Data caching Group management Event detection Data subscription Scheduling 12

13 CLMF[5] Cluster-Based Lightweight i Middleware Framework Virtual machine with two layers Resource management Resides on cluster head Cluster Distributed among all sensor nodes Includes cluster forming and control protocols Issues resource management commands 13

14 MSM[7] Middleware Service for Monitoring Operates between the transport layer and applications Divides WSN in two regions Dominant Contains a gateway (an intelligent coordinator) acting as a central access point Provides connectivity to the transit network Nondominant Core components include data distribution and monitoring services Used to communicate among devices in WSN Uses an ORB as an interface Not flexible to adjust to a variety of applications 14

15 Em*[9] A software environment for deploying wireless sensor network applications on Linux-based platforms Incorporates tools and services to create WSN applications Can be used to support: Deployment Simulation Emulation Visualization 15

16 Impala[10] Lightweight middleware and API for sensor application adaptation and update Has an event-driven architecture; 5 types of events: Timer, packet, send done, data, and device failure Intended to act as an OS, resource manager, and event filter Has three layers Application layer Adapts applications to various runtime conditions Application adapter Receives and propagates software updates and installs them Event filter Captures and dispatches events to the application updater 16

17 DFuse[11] Middleware only for data fusion For programming fusion applications Focuses on decision making based on 17 Data and information acquired, filtered, and correlated with other relevant information Comprises A data fusion API A distributed algorithm for energy-aware role assignment

18 Device Database System DDS[12] Enables query processing over a device network Supports query types: Historical Snapshot Long-running 18

19 SensorWare[13] [3] Provides a language and runtime environment to support WSN programming d l i d i l di ib d Language model is used to implement a distributed algorithms 19

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