{"id":183060,"date":"2007-03-21T00:00:00","date_gmt":"2009-10-31T10:16:40","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/energy-conservation-techniques-in-mobile-delay-tolerant-sensor-networks\/"},"modified":"2016-09-09T09:43:26","modified_gmt":"2016-09-09T16:43:26","slug":"energy-conservation-techniques-in-mobile-delay-tolerant-sensor-networks","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/energy-conservation-techniques-in-mobile-delay-tolerant-sensor-networks\/","title":{"rendered":"Energy Conservation Techniques in Mobile Delay-Tolerant Sensor Networks"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Mobile delay-tolerant sensor networks are becoming increasingly important because of their ability to deliver long periods of fine-grained sensing over a wide area with a small number of nodes. A key challenge in these systems, however, is that nodes are extremely energy constrained since they must be small, lightweight, and function autonomously for months at a time. This problem is compounded by the fact that mobile nodes demand radios with relatively long ranges to maximize the effectiveness of short, infrequent communication periods.<\/p>\n<p>This presentation will introduce my dissertation on energy conservation techniques for these networks. The talk will primarily focus on a family of lossless compression algorithms tailored to sensor networks. These algorithms include a novel LZW variant that exploits characteristic patterns of sensor data to reduce energy consumption by more than 40% as well as further data transforms that can take advantage of the structure of the data to decrease energy consumption by nearly a factor of three.<\/p>\n<p>Then, this presentation will briefly introduce a data abstraction layer for mobile sensor networks that reorganizes data from the network&#8217;s viewpoint. This organization facilitates the development of services for data identification, search, and reduction, which combine to save energy by making communications more efficient.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Mobile delay-tolerant sensor networks are becoming increasingly important because of their ability to deliver long periods of fine-grained sensing over a wide area with a small number of nodes. A key challenge in these systems, however, is that nodes are extremely energy constrained since they must be small, lightweight, and function autonomously for months at [&hellip;]<\/p>\n","protected":false},"featured_media":194878,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_hide_image_in_river":0,"footnotes":""},"research-area":[],"msr-video-type":[],"msr-locale":[268875],"msr-post-option":[],"msr-session-type":[],"msr-impact-theme":[],"msr-pillar":[],"msr-episode":[],"msr-research-theme":[],"class_list":["post-183060","msr-video","type-msr-video","status-publish","has-post-thumbnail","hentry","msr-locale-en_us"],"msr_download_urls":"","msr_external_url":"https:\/\/youtu.be\/3_RedVLUuMY","msr_secondary_video_url":"","msr_video_file":"","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/183060","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-video"}],"version-history":[{"count":0,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/183060\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/194878"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=183060"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=183060"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=183060"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=183060"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=183060"},{"taxonomy":"msr-session-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-session-type?post=183060"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=183060"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=183060"},{"taxonomy":"msr-episode","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-episode?post=183060"},{"taxonomy":"msr-research-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-theme?post=183060"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}