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Sensor Networks Purnima Chandrasekaran April 27, 2000 Why Sensor Nets? • Civilian: – Embed numerous distributed devices to monitor and interact with physical world: in work-spaces, hospitals, homes, vehicles, etc. – Inventory monitoring in factories. – Map disaster stricken areas and coordinate recovery plans. – Monitoring traffic conditions. • Military: – Stealthy monitoring of hostile / inhospitable terrain. – Detect presence of biological agents in a battlefield. – Perimeter surveillance 4/27/00 SensorNets 2 Overview • Sensors : – small wireless low-power unattended sensing devices with limited communication & computation capabilities. • SensorNets: – Large scale dynamically changing robust sensor colonies. – Coordinate amongst themselves to establish a communication network and achieve a larger sensing task. • Eg: Multiple sensors work together to find the speed, direction, size, etc. of an approaching vehicle. – As sensors are distributed, sensor network applications are designed using distributed algorithms. 4/27/00 SensorNets 3 Constraints • Energy • Fault-tolerant – Very limited (May not be recharged :-) – Avoid communication over long distances. • Self-configuring • Dynamic Environments – Sheer-number of sensors make individual configuration impossible. – Sensors must reorganize when additional sensors are added or when old sensors fail. 4/27/00 – Sensors fail due to inhospitable environments. – SensorNets should be tolerant of node failures. – Dynamic operating conditions – Dynamic resource availability – Dynamic tasks • Unattended and untethered operation. SensorNets 4 Comparison with Mobile Networks SensorNets Mobile Networks Nodes are unattended. Mobile nodes are mostly attended. Cheap sensors require inexpensive power sources. Sensor life ends when power runs out. Large numbers of sensors coordinate to perform a task. Configuration of individual sensors is infeasible. Designed for a specific application. Communication is data-centric. Energy must be conserved, but nodes can be recharged. 4/27/00 Mobile nodes independently offer service to the user. Mobile node can be configured by the user. Designed to offer a wide-variety of services. Communication is addressed to node. SensorNets 5 Aspects of SensorNet Design • Addressing – Global Vs Local • Naming and Binding • Clustering – To efficiently coordinate local interactions to achieve global goals • Information Dissemination – Directed Diffusion – Negotiation based 4/27/00 SensorNets 6 Address-Free Architecture • Applications do not address a particular sensor: – What is the temperature at sensor #89768? – Where are nodes whose temperature recently exceeded 30º? • • • • Nodes and data are described by attributes rather than addresses. Addressing, routing, and naming are removed from network layer to application layer. Addresses in Internet serve two purposes: Routing and Identity In SensorNets – nodes are not individually identified/addressed – Message routing is Application specific – Addresses do not serve the same purpose as traditional networks. 4/27/00 SensorNets 7 Address-Free Architecture (contd.) • Global addresses require long addresses to address individual nodes – Amount of data communicated is small, but addressing overhead is high – Power limitations impose local communication (but, sensing task is distributed) – Locally unique identifiers require far fewer bits => Address Scalability • • • • Locally unique identifiers - ephemeral, randomly selected, probabilistically unique identifier Conflicts are resolved by generating a new identifier Detection of identifier collision is application-specific & is achieved by detecting inconsistencies in data (eg. Missing sequence numbers) Identifiers provide continuity among packets that make up a logical transaction 4/27/00 SensorNets 8 Clustering • Clustering allows local coordination to achieve global goals. – Scales well as the number of sensors increases – Improved Robustness – Efficient resource utilization • Clustering builds hierarchical parent-child relationships – Cluster-heads (parents) summarize the sensing information of children – To conserve power, they may be the only ones performing some tasks • Clustering Algorithm: – Initially, all sensors are at level 0. – Run a link level procedure to minimize transmission power, that still provides full network connectivity. – Each sensor follows the following algorithm: 4/27/00 SensorNets 9 Clustering Algorithm (contd.) • Send an advertisement with a hop count ‘h’. – Advertisements include hierarchical level, parent ID, remaining power • Wait for time ‘t’ proportional to ‘h’ • Receive other sensor advertisements during ‘t’ • After ‘t’ , start a promotion timer ‘p’ – ‘p’ is inversely proportional to power left and advertisements received • At the end of ‘p’, sensor promotes itself to level 1. • Advertise itself as parent to level 0 sensors. – includes a list of sensors it heard from; only they accept this as parent – Symmetric connectivity between parent and child • This process repeats at level 1, 2,... => setting up the hierarchy 4/27/00 SensorNets 10 Example: Triangulation • Cluster heads independently run the following algorithm: – Each sensor determines its location and the general direction of target. – If all the neighboring cluster-heads fall on the same side w.r.t. the target, the cluster-head participates in triangulation. – A and B participate, while X excludes itself. 4/27/00 SensorNets 11 Example 2: Adaptive Fidelity • To get a better picture, turn on more sensors. – Nodes adjust their coverage, sampling rate, communication frequency based on neighbor density, power levels, and reports from direct neighbors, etc. 4/27/00 SensorNets 12 Negotiation Based Protocols for Information Dissemination • Sensor Protocols for Information via Negotiation (SPIN) – used to disseminate information in a sensor network • • • • • Data is named & negotiated using • high-level descriptors - meta data Data is also routed in application controlled & application specific ways based on data layout and state of • resources at sensors Format of meta-data is application specific 4/27/00 SensorNets If x is the meta-data for data X, then sizeof(x) < sizeof(X) If data are distinguishable => metadata should also be distinguishable Overcome implosion, overlap and resource blindness deficiencies of classic flooding – By negotiation & resource-adaptation Two classes of SPIN protocols– SPIN-PP for point-to-point networks – SPIN-BC for broadcast networks 13 SPIN (contd.) • Messages for communication in SPIN: – ADV new data advertisement – REQ request for data – DATA data message • ADV & REQ contain only meta-data 4/27/00 SensorNets 14 SPIN - PP • • • • • • 4/27/00 SensorNets SPIN-PP is a simple protocol Nodes know only about 1-hop neighbors Doesn’t involve much computation to make decisions Changes in network topology have to travel only 1-hop Can run in an unconfigured network with a small startup to determine 1hop neighbors SPIN-EC is SPIN-PP optimized for energy conservation 15 SPIN - BC • • • • • • 4/27/00 Improvement over SPIN-PP as it uses 1-to-many communication Effective resource conservation by broadcast-message suppression Nodes set a timer on receiving an ADV and send a REQ only if no other REQ is overheard for the same data. SPIN-RL reliable version of SPIN-BC Each node keeps track of every advertisement & re-requests if data is not received within some period of time Re-requests a randomly picked destination from the list of neighbors that advertised the piece of data SensorNets 16 Conclusions • Sensor Networks is a very recent technology with lots of research being carried out. • Several approaches to solving the various issues have been proposed and simulations done to study their effectiveness. • Every approach has many advantages and disadvantages and may/ many not be suitable for a particular implementation of Sensor network. 4/27/00 SensorNets 17 References • • • • Jeremy Elson, Deborah Estrin, “An Address-Free Architecture for Dynamic Sensor Networks,” Under submission to SIGCOMM 2000. Joanna Kulik, W Heinzelman, Hari Balakrishnan, “Negotiation-based Protocols for Disseminating Information in Wireless Sensor Networks,” ACM Mobicom’99. Deborah Estrin, Ramesh Govindan, John Heidemann, Satish Kumar,“Next Century Challenges: Scalable Coordination in Sensor Networks,” ACM Mobicom’99. William Adjie-Winoto, Elliot Schwatz, Hari Balakrishnan, “The design and implementation of an intentional naming system,” ACM SOSP ‘99. 4/27/00 SensorNets 18