2026-09-19T01:25:42Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/343682022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Karen Sollins.
Fertis, Apostolos
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2006-11-07T11:49:04Z
2006-11-07T11:49:04Z
2005
http://hdl.handle.net/1721.1/34368
70079317
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, September 2005.
"June 2005."
Includes bibliographical references (p. 123-125).
The field of sensor networks is rapidly developing enabling us to deploy them to an unpredictable environment and draw diverse and interesting information from it. Their capabilities are improving. They can sense complicated phenomena, they take measurements for several attributes, they make numerous computations and they communicate large amounts of information. Most sensors are battery operated and in most cases they are not easily rechargeable, as the environment in which they are located is not easily accessible. Thus, they have limited energy, which should be used to draw out as much useful information as possible. Moreover, quite often we need to receive data from a sensor network at a high rate. In order to be able to manage energy and time efficiently in sensor networks, we have to develop protocols that synchronize the cooperation among sensors and send information to the targets as quickly as possible and with low energy consumption. In many cases, the whole set of values that are measured is not required by the query which is submitted to the network. The query asks for an aggregate over the measurements. The propagation of all measured values to a central computation point is resource consuming. Tiny AGgregation (TAG) provides an algorithm to compute aggregates by merging and forwarding partial results. The merging is done in the internal nodes of the routing tree that is formed. Sometimes, the aggregation is applied over a subset of the measurements. Furthermore, the wireless links that connect the sensor nodes are not characterized by the same congestion. This fact makes the energy spent for transmission across a link varying.
In addition, the use of links with high congestion in the routing tree delays the propagation of partial records to the root and thus, increases the response time. The protocol SYMPHONY provides an improvement on the TAG algorithm. It forms a Steiner tree that spans the sensors that participate in the aggregate and has cost which does not exceed the double of the optimal Steiner tree cost for the connectivity graph. The Expected Transmission Count (ETX) and the latency metrics are used for the links. The communication and energy cost of forming the SYMPHONY routing tree is proved to be polynomial in the number of nodes. The construction cost can be reduced if the requirements for the cost in the resulting routing tree are relaxed. In any case, the use of SYMPHONY can save much energy, if the aggregate is computed in a frequent rate.
by Apostolos Fertis.
S.M.
125 p.
6573564 bytes
6579912 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Assembling regions for efficacious aggregate query processing in wireless sensor networks
Thesis
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<Abstract>The field of sensor networks is rapidly developing enabling us to deploy them to an unpredictable environment and draw diverse and interesting information from it. Their capabilities are improving. They can sense complicated phenomena, they take measurements for several attributes, they make numerous computations and they communicate large amounts of information. Most sensors are battery operated and in most cases they are not easily rechargeable, as the environment in which they are located is not easily accessible. Thus, they have limited energy, which should be used to draw out as much useful information as possible. Moreover, quite often we need to receive data from a sensor network at a high rate. In order to be able to manage energy and time efficiently in sensor networks, we have to develop protocols that synchronize the cooperation among sensors and send information to the targets as quickly as possible and with low energy consumption. In many cases, the whole set of values that are measured is not required by the query which is submitted to the network. The query asks for an aggregate over the measurements. The propagation of all measured values to a central computation point is resource consuming. Tiny AGgregation (TAG) provides an algorithm to compute aggregates by merging and forwarding partial results. The merging is done in the internal nodes of the routing tree that is formed. Sometimes, the aggregation is applied over a subset of the measurements. Furthermore, the wireless links that connect the sensor nodes are not characterized by the same congestion. This fact makes the energy spent for transmission across a link varying.</Abstract>
<Abstract>In addition, the use of links with high congestion in the routing tree delays the propagation of partial records to the root and thus, increases the response time. The protocol SYMPHONY provides an improvement on the TAG algorithm. It forms a Steiner tree that spans the sensors that participate in the aggregate and has cost which does not exceed the double of the optimal Steiner tree cost for the connectivity graph. The Expected Transmission Count (ETX) and the latency metrics are used for the links. The communication and energy cost of forming the SYMPHONY routing tree is proved to be polynomial in the number of nodes. The construction cost can be reduced if the requirements for the cost in the resulting routing tree are relaxed. In any case, the use of SYMPHONY can save much energy, if the aggregate is computed in a frequent rate.</Abstract>
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