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Enhancing Context-Awareness with Cloudlets in Mobile Computing

The future of context-awareness relies on high data rate sensors and robust solutions to support applications in health, advertising, gaming, travel, and education. Current systems struggle with low accuracy and latency issues. Cloudlets offer a solution by bringing cloud capabilities closer to users, reducing latency and improving responsiveness. This paper discusses the architecture of cloudlets, their integration with access points, and the challenges of providing privacy, execution integrity, and seamless execution migration between devices, paving the way for innovative business models.

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Enhancing Context-Awareness with Cloudlets in Mobile Computing

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  1. Context-awareness, cloudlets and the casefor AP-embedded, anonymous computing Anthony LaMarcaAssociate DirectorIntel Labs Seattle

  2. Context Awareness • Is driving the next generation of applications and services • Health & assisted living, advertising, gaming, travel, social networking, task assistance and education, etc… • Is currently driven by low data rate sensors • Accelerometers, RFID and radio base station IDs, thermocouples, barometers, and capacitive sensors

  3. The Future of Context Awareness • SOA is not accurate or robust enough for many applications • Location: 5-100 meters error, no pose or direction info • Activity: 20-40% error rates unless drastically limited in scope • Next gen context aware solutions • High data rate sensors (Cameras and microphones) • Compute intensive (real time classification & online learning) • Interactive • Puts huge pressure on mobile devices in termsof compute capacity, communication, and power budget

  4. Supporting Mobile Context Awareness The Case for VM-based Cloudlets in Mobile ComputingSatyanarayanan, Bahl, Caceres, Davies • The cloud isn’t the solution • Too much latency for real-time responsiveness (Internet2 mean RTT 50-250 ms) • Bring the cloud closer • Cloudlet: “data center in a box” • One network hop from the client • Shared with other nearby clients

  5. Put the cloudlet into the Access Point • Lots of cores with no power constraints one network hop away • Forms a natural rendezvous point between the cloud and the client • Trusted by both parties and lies within trusted boundary of the client (AP in the home or coffee shop) • Leverage existing 802.11 protocols for service discovery, encryption, billing and authentication with no extra overhead • Provides tight coupling between the network and the computation • Incremental deployment • Today APs are added as business, home usage grow • Cloudlet capabilities could be incrementally added with cloudlet-APs 802.11n AP with a n-core CPU • Low latency, high bandwidth

  6. Challenges • Providing mechanisms to guarantee execution integrity • Privacy: Client should trust that no sensitive data is retained • Correctness of execution: Clients and service provider should trust the correctness of the computation • Approach: Leverage trusted hardware primitives of Dynamic Root of Trust for Measurement (DRTM) and attestation • Developing applications that span the client, AP and cloud • Seamless migration of execution between the client, AP and the cloud • Supporting flexible business models • Give users access to proprietary algorithms in exchange for context • Provide micropayments to cloudlet owners in exchange for cycles • Broker connections between advertisers and customers based on conetxt

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