Wireless sensor networks (WSNs) face significant scalability challenges due to the proliferation of wide-area wireless monitoring and control systems that require thousands of sensors to be connected over long distances. Due to their short communication range, existing WSN technologies such as those based on IEEE 802.15.4 form many-hop mesh networks complicating the protocol design and network deployment. To address this limitation, we propose a scalable sensor network architecture – called Sensor Network Over White Spaces (SNOW) – by exploiting the TV white spaces. Many WSN applications need low data rate, low power operation, and scalability in terms of geographic areas and the number of nodes. The long communication range of white space radios significantly increases the chances of packet collision at the base station. We achieve scalability and energy efficiency by splitting channels into narrowband orthogonal subcarriers and enabling packet receptions on the subcarriers in parallel with a single radio. The physical layer of SNOW is designed through a distributed implementation of OFDM that enables distinct orthogonal signals from distributed nodes. Its MAC protocol handles subcarrier allocation among the nodes and transmission scheduling. We implement SNOW in GNU radio using USRP devices. Experiments demonstrate that it can correctly decode in less than 0.1ms multiple packets received in parallel at different subcarriers, thus drastically enhancing the scalability of WSN.<\/p>\n","protected":false},"excerpt":{"rendered":"
Wireless sensor networks (WSNs) face significant scalability challenges due to the proliferation of wide-area wireless monitoring and control systems that require thousands of sensors to be connected over long distances. Due to their short communication range, existing WSN technologies such as those based on IEEE 802.15.4 form many-hop mesh networks complicating the protocol design and […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13547],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-341108","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"ACM","msr_edition":"SenSys","msr_affiliation":"","msr_published_date":"2016-11-16","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"Top 3 Papers","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"341111","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"snow-sensys2016","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/12\/SNOW-sensys2016.pdf","id":341111,"label_id":0}],"msr_related_uploader":"","msr_attachments":[],"msr-author-ordering":[{"type":"text","value":"Abusayeed Saifullah","user_id":0,"rest_url":false},{"type":"text","value":"Mahbubur Rahman","user_id":0,"rest_url":false},{"type":"text","value":"Dali Ismail","user_id":0,"rest_url":false},{"type":"text","value":"Chenyang Lu","user_id":0,"rest_url":false},{"type":"user_nicename","value":"ranveer","user_id":33344,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=ranveer"},{"type":"user_nicename","value":"liuj","user_id":32707,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=liuj"}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[],"msr_project":[239387,171068,170158],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":239387,"post_title":"FarmBeats: AI, Edge & IoT for Agriculture","post_name":"farmbeats-iot-agriculture","post_type":"msr-project","post_date":"2016-06-16 20:10:17","post_modified":"2024-08-29 22:15:59","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/farmbeats-iot-agriculture\/","post_excerpt":"Our goal is to enable data-driven farming. We believe that data, coupled with the farmer's knowledge and intuition about his or her farm, can help increase farm productivity, and also help reduce costs. However, getting data from the farm is extremely difficult since there is often no power in the field, or Internet in the farms.","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/239387"}]}},{"ID":171068,"post_title":"Dynamic Spectrum and TV White Spaces","post_name":"dynamic-spectrum-and-tv-white-spaces","post_type":"msr-project","post_date":"2012-11-30 10:07:58","post_modified":"2022-10-11 15:37:52","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/dynamic-spectrum-and-tv-white-spaces\/","post_excerpt":"The Spectrum Opportunity Microsoft is working with key partners around the world to ensure consumers have access to an increasing range of connected devices. To meet growing consumer demand and address other policy challenges, we must consider multiple approaches which can be used that enable opportunistic, dynamic use of spectrum. Real World Stories While innovative uses of the radio spectrum \u2013 the building blocks of wireless connectivity \u2013 drive economic development, new business growth, policy…","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/171068"}]}},{"ID":170158,"post_title":"Networking Over White Spaces (KNOWS)","post_name":"networking-over-white-spaces-knows","post_type":"msr-project","post_date":"2008-12-19 20:10:09","post_modified":"2021-04-12 22:35:02","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/networking-over-white-spaces-knows\/","post_excerpt":"The next generation of wireless networks will include software defined radios, cognitive radios, and multi-radio systems which will co-exist harmoniously while operating over a very wide range of frequencies. Under the umbrella of the KNOWS project we are revisiting \"classical\" wireless networking problems and designing new solutions that incorporate and build upon recent advances in software and hardware technologies for networking over the recently opened white spaces spectrum. Brief Description The WhiteFiService APIs and web…","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/170158"}]}}]},"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/341108"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-research-item"}],"version-history":[{"count":1,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/341108\/revisions"}],"predecessor-version":[{"id":410651,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/341108\/revisions\/410651"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=341108"}],"wp:term":[{"taxonomy":"msr-content-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-content-type?post=341108"},{"taxonomy":"msr-research-highlight","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-highlight?post=341108"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=341108"},{"taxonomy":"msr-publication-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publication-type?post=341108"},{"taxonomy":"msr-product-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-product-type?post=341108"},{"taxonomy":"msr-focus-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-focus-area?post=341108"},{"taxonomy":"msr-platform","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-platform?post=341108"},{"taxonomy":"msr-download-source","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-download-source?post=341108"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=341108"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=341108"},{"taxonomy":"msr-field-of-study","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-field-of-study?post=341108"},{"taxonomy":"msr-conference","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-conference?post=341108"},{"taxonomy":"msr-journal","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-journal?post=341108"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=341108"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=341108"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}