Ben Miller.  A distributed algorithm is a type of parallel algorithm  They are designed to run on multiple interconnected processors  Separate parts.

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Presentation transcript:

Ben Miller

 A distributed algorithm is a type of parallel algorithm  They are designed to run on multiple interconnected processors  Separate parts of the algorithm are run simultaneously on independent processors

 Each of the processors has its own memory  The processors send messages to each other

 Wireless Sensor Networks are made up of a series of distributed sensors  The sensors collect data and pass it through the network  The sensors are designed to consume very little power

 Each sensor node typically consists of a microcontroller, radio, and battery

 Golden Gate Bridge ◦ Accelerometers are used to collect data on the bridge’s movement to monitor its structural health ◦ Researchers at the University of California at Berkeley used 64 sensor nodes to monitor vibrations

 Volcano Monitoring ◦ Sensors can be used to observe seismic events ◦ Nodes compare when they observe events to determine their location ◦ Allows geologists to collect data from large areas that are dangerous and difficult to access

◦ Researchers from Harvard used a network of 16 sensors to monitor a volcano in Ecuador. ◦ In a period of 19 days, they recorded 229 earthquakes, eruptions, and other seismic events

 Datacenter Provisioning ◦ Datacenters use a lot of energy and the computers produce a lot of heat ◦ Wireless Sensor Networks allow datacenters to determine which machines need cooling ◦ Making these dynamic adjustments can greatly reduce power consumption

 Other applications include: ◦ Environment and habitat monitoring ◦ Wildfire detection ◦ Battlefield surveillance Wireless Sensor Networks have become a popular research area in computer science due to the wide range of applications

 One of the challenges in the field of sensor networks is the deployment of the sensors  The sensors must be properly spaced  If the sensors are too close to each other they won’t cover the entire area of interest  If the sensors are too far apart the coverage regions won’t overlap and the network could become partitioned

 Inspired by the equilibrium of molecules, which minimizes electronic energy  Each node tries to find its lowest energy point  When each node has found its lowest energy point, the nodes should be uniformly spread across the area of interest

 A node’s movement is based on the combined forces acting on it due to its neighboring nodes.

The algorithm has 4 parts:  1: Initialization  2: Partial Force Calculation  3: Oscillation Check  4: Stability Check  Parts 2,3, and 4 repeat until the node stops moving

 Initial locations and sensing ranges are initialized  Local density is the number of nodes within its cR  Expected density is the number of nodes required to cover the entire area when the nodes are deployed uniformly

 The force depends on the distance between the nodes and the node’s current local density  High local density will cause the force to be high

 Oscillation is when a node is moving back and forth in the same spot  Counts the number of oscillations, if it is over the limit the node stops

 If a node moves less than the threshold during the time duration, stability_limit,  the node is considered to be in its final position

 Each node goes through the four steps until it stops moving. This results in the sensors being uniformly distributed.  The movement of each node is affected by the position of its neighboring nodes. If one node moves, the surrounding nodes will also move to maximize coverage and uniformity

 Mobile Data Gathering

 Mobile Sensor Networks are a rapidly growing field with a wide range of applications  As distributed systems, like sensor networks, continue to become more popular, the demand for distributed algorithms will increase

 Golden Gate Bridge Study: S. Kim, S. Pakzad, D. Culler, J. Demmel, G. Fenves, S. Glaser, and M. Turon. Health monitoring of  civil infrastructures using wireless sensor networks. In IPSN ’07: Proceedings of the 6th international  conference on Information processing in sensor networks, 2007  Volcano Study: G. Werner-Allen, K. Lorincz, J. Johnson, J. Leess, and M. Welsh. Fidelity and yield in a  volcano monitoring sensor network. In 7th USENIX Symposium on Operating Systems Design and  Implementation (OSDI),  Lenzen, Christoph. "Distributed Algorithms for Sensor Networks." Hebrew University of Jerusalem .  Zhao, Miao and Yang, Yuanyuan. “Optimization-Based Distributed Algorithms for Mobile Data Gathering in Wireless Sensor Networks.”  Heo, and Varshney. “Energy-Efficient Deployment of Intelligent Mobile Sensor Networks” 