Presentation on theme: "Research issues in wireless Sensor networks Presented by: Brajendra Kumar Singh Course: Wireless Communications Systems 88-563 Winter 2007 Semester Instructor:"— Presentation transcript:
Research issues in wireless Sensor networks Presented by: Brajendra Kumar Singh Course: Wireless Communications Systems Winter 2007 Semester Instructor: Dr. Kemal E. Tepe Department of electrical and computer engineering University of Windsor, Windsor, Ontario, Canada
Introduction Wireless sensor network: Massively distributed, untethered, and unattended systems to cover spatially distributed phenomena in natural & obstructed environments A sensor node is a Single-chip systems with Low-power CPU and less memory, Radio or optical communication MEMs-based on-chip sensors Referred to as “motes” or “smart dust” Mote applications are deeply tied to hardware Each mote runs a single application at a time. Driven by interaction with environment Event arrival and data processing are concurrent activities Reliability It must collect data without human interaction for months at a time. No real recovery mechanism in the field except for automatic reboot. In-network processing Self configuring system
Sensor nodes scattered in a sensor field The components of a sensor node Source: Ref
Example of some sensors Source: Ref
OS and Programming TinyOS designed for network embedded systems. the core OS requires 400 bytes of code and data memory, combined. a component-based architecture, a simple event-based concurrency model nesC nesC is an extension of C Whole-program analysis nesC is a static language nesC supports and reflects TinyOS’s design two types of components in nesC: modules and configurations. Simulators: Tossim Emstar Others: Shawn, VisualSense, J-Sim etc.
Group of sensor nodes in action Source: Ref
Sensors on field Base Station Source: Ref
Tight resource constraints Energy Communications range, bandwidth Computation, storage (but not as constrained as energy and communications – computation is often used to reduce communication) Dynamically changing network topology Battery depletion Node failure Node mobility Unreliable links (noise, jamming) Dynamically changing bandwidth, range, and computation power Interactions Computation constraints lead to uneven power depletion which leads to network topology changes Correlated bursts of traffic across neighboring nodes not a collection of independent point-to-point flows violating the design assumptions of common media access protocols Wireless transmission is unreliable Sensor Network Challenges
Factors influencing design of WSN Fault tolerance, Scalability, Production costs, Operating environment, Sensor network topology, Hardware constraints, Transmission media, Power consumption Data Management Geographic routing challenges Monitor and Maintenance
Sensor network model
THE PHYSICAL LAYER OPEN RESEARCH ISSUES Modulation schemes: Simple and low-power modulation schemes needed can be either baseband or passband Solution Strategy: overcome signal propagation effects Hardware design: Tiny, low-power, low-cost transceiver, sensing, and processing units needed Power-efficient hardware management strategies Solution Strategy: managing frequencies of operation reducing switching power predicting work load in processors
DATA LINK LAYER OPEN RESEARCH ISSUES MAC for mobile sensor networks: Self-Organizing Medium Access Control for Sensor Networks (SMACS) and the Eavesdrop-And-Register (EAR) Algorithm perform well for mainly static sensor networks. It is assumed in the connection schemes that a mobile node has many static nodes as neighbors. In CSMA-based scheme, the mobility issues and carrier sensing mechanisms remain largely unexplored. Determination of lower bounds on the energy required for sensor network self-organization Error control coding schemes: Convolution coding effects have been explored. The feasibility of other error control schemes in sensor networks needs to be explored. Power-saving modes of operation: a sensor node must enter into periods of reduced activity when running low on battery power. The enumeration and transition management for these nodes is open to research.
NETWORK LAYER OPEN RESEARCH ISSUES Existing protocols need to be improved or new protocols developed to address higher topology changes higher scalability An overview of network layer schemes
Exploit Redundancy Tiered Architectures Exploit spatial diversity and density of sensor networks Achieve desired global behavior with adaptive localized algorithms Leverage data processing inside the network and exploit computation near data sources Time and location synchronization Self-configuration Secure routing Source: Ref Open Research Issues for routing NETWORK LAYER Continued….. Fruits are not so low in the Routing research area
TRANSPORT LAYER OPEN RESEARCH ISSUES Acknowledgments are too costly (As needed in TCP/IP) Split the end-to-end communication UDP-type protocols are used in the sensor network traditional TCP/UDP protocols in the Internet or satellite network
THE APPLICATION LAYER Open research issues Three possible protocols Sensor Management Protocol (SMP), Task Assignment and Data Advertisement Protocol (TADAP) Sensor Query and Data Dissemination Protocol (SQDDP) SQDDP is explored a lot, but SMP and TADAP are still open for research.
Routing Algorithms with secure foundations Optimize Secure Data Management Algorithms (Aggregation) Social and Network privacy Mobile nodes, Mobile Base Stations Delegation of privileges Tolerate the lack of physical security Intrusion Detection techniques, integrated IDS Efficient Data Dissemination Protocols Reliable Transport Protocols Congestion Control and Avoidance Techniques Sensor Network Measurements Open Research Areas - 1
Programming models, architectures, tools Programming abstractions, service architecture, resource mgmt Computing with uncertainties Uncertainties about environment and system itself Models of reliability, resource-aware and task-oriented computation, software architectures Consider both application and networking Simultaneously Vs Separately Quality of service guarantees built in to the network protocols Real-time support in sensor networks - Network support for classes of traffic not for specific applications - Precise network provisioning not realistic in sensor networks Innovative applications In areas such as security, transportation, healthcare Open Research Areas - 2
Scheduling Challenges Uncertainty: nondeterministic processing algorithms, communication noise Dynamics: robustness to topology and resource changes Deep, multi-hop data flows Scale Providing decision-theoretic objective tradeoffs Some Approaches to Handling Scheduling Problems Static schedules that are robust to uncertainty and time-varying constraints Network provisioning for redundant paths On-line scheduling - Not practical in tight computation nodes - Introduces latency Off-line construction of conditional schedules that adapt to sensor feedback, topology changes, and task changes Open Research Areas - 3
Integrated Communication and Computation Scheduling Problem (Load balancing problem) Parallel, distributed computation Sensor processing Task data flow, e.g. aggregation, in-network processing Communication Broadcast links: interference, range Synchronization of computation and communication to satisfy task Objective Function: Minimize computation convergence time Minimize computation convergence time Minimize latency in responding to new sensor data Minimize latency in responding to new sensor data Minimize total energy consumed Minimize total energy consumed Balance distribution of energy consumed Balance distribution of energy consumed Open Research Areas - 4
Sensor Applications Just the tip of the iceberg o A Wireless Sensor Network for Structural Monitoring o For monitoring health of power lines o Smart paint o Wireless Sensor Networks for Habitat Monitoring o Biomedical Sensors o Military surveillance
Conclusion Optimize, Optimize, Optimize! (memory constraints, energy usage…)
References 1.Ian Akyildiz., W. Su, Y. Sankarasubramaniam, E. Cayirci, "A Survey on Sensor Networks", IEEE Communications Magazine, August David Culler, Deborah Estrin, and Mani Srivastava, "Overview of Sensor Networks", IEEE Computer, August Chee.-Yee. Chong and Kumar, S.P., "Sensor Networks: Evolution, Opportunities, and Challenges," Proc IEEE, August David Gay, Phil Levis, Rob von Behren, Matt Welsh, Eric Brewer, and David Culler, "The nesC Language: A Holistic Approach to Networked Embedded Systems", Programming Language Design and Implementation (PLDI) 2003, June Al-Karaki, J.N. Kamal, A.E., Routing techniques in wireless sensor networks: a survey, Wireless Communications, Volume 11, Issue 6, Dec Deepak Ganesan, Alberto Cerpa, Wei Ye, Yan Yu,Jerry Zhao, Deborah Estrin, "Networking Issues in Wireless Sensor Networks" Slides Slides internet, 2005
Thanks Questions and suggestions?
Some facts TinyDB a sensor network query processing engine, Mate a small virtual machine that allows rapid reprogramming of sensor networks. nesC Vs C: C does have significant disadvantages: it provides little help in writing safe code or in structuring applications. nesC addresses safety through reduced expressive power and structure through components.
Differences between sensor networks and ad hoc networks are: The number of sensor nodes in a sensor network can be several orders of magnitude higher than the nodes in an ad hoc network. Sensor nodes are densely deployed. Sensor nodes are prone to failures. The topology of a sensor network changes very frequently. Sensor nodes mainly use a broadcast communication paradigm, whereas most ad hoc networks are based on point-to-point communications. Sensor nodes are limited in power, computational capacities, and memory. Sensor nodes may not have global identification (ID) because of the large amount of overhead and large number of sensors.
Transmission media based on RF circuit design The uAMPS wireless sensor node uses a Bluetooth- compatible 2.4 GHz transceiver with an integrated frequency synthesizer. The low-power sensor device uses a single-channel RF transceiver operating at 916 MHz. based on infrared. Infrared communication is license-free robust to interference from electrical devices. cheaper and easier to build. Smart Dust mote computing Both infrared and optical require a line of sight between the sender and receiver.
Power Consumption A limited power source (< 0.5 Ah, 1.2 V). Power-aware protocols and algorithms for sensor networks. The main task of a sensor node detect events, perform quick local data processing transmit the data Power consumption can hence be divided into three domains: sensing communication data processing
Embaded Network Sensing Research focus Network Self- Organization Programmingmodels Database policies and architecture Sensors Connection to infrastructure Cooperative Detection CommunicationLinks Theoreticalframework Node Localization Mobility and navigation Target Identification Algorithms System Energy Management Actuation Humaninterface Modeling of Environment Calibration