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This presentation outlines the challenges and solutions in sensor networks, covering topics such as Directed Diffusion and SPIN protocols, sensor node capabilities, applications, and future research directions. Explore how Directed Diffusion enhances scalability, energy efficiency, and robustness in data dissemination while SPIN protocols focus on negotiation and resource adaptation. Discover the importance of efficient communication paradigms for monitoring remote locations and environments. Gain insights into the evolving field of sensor networks and the potential for future deployments.
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Data Dissemination in Sensor Networks Challenges and Solutions by Sovrin Tolia
Presentation Outline • Overview of Sensor Networks • Directed Diffusion, A Scalable and Robust Communication Paradigm for Sensor Networks • SPIN, Adaptive Protocols for Information Dissemination in Wireless Sensor Networks
Research Efforts • Directed Diffusion USC/ISI Institute Deborah Estrin, Ramesh Govindan et al • SPIN Protocols MIT Balakrishnan, Joanna Kulik et al
Challenges in Sensor Networks • Sheer Numbers • Unattended deployment • Device failures • Frequent Change • Heterogenity of Tasks
Sensor Nodes • Capability of Sensor Nodes • Distributed Microsensing • Sensor Networks are task specific • Autonomous Operation
Sensor Network Applications • Monitoring Remote Geographic Locations and terrains • Toxic Urban Locations • Less Accessible environments like large Industrial Plants and Aircraft Interiors
Directed Diffusion • Motivated by Scalability, Energy Efficiency and and robustness • Data Centric • Application Aware • Energy Efficient • Remote Surveillance Sensor Network
Directed Diffusion • Naming
Directed Diffusion • Interests and Gradients Sink Nodes Periodic Broadcasts Interest Cache in every node (distinct interests) Two Way Gradient established Generalized Interest Propagation means
Directed Diffusion • Data Propagation location satisfied, finds Interest Match from cache computes the highest data rate in gradients present in the interest cache Intermediate Node base their decision based on Data cache “Downconversion”
Directed Diffusion • Reinforcement Data Driven Rules for deciding which node(s) to reinforce Explicitly send a high data rate Interest message What do the neighboring nodes do Extreme Reactivity and Negative Reinforcements
In Essence • No mention of target detection algos • The usage is not restricted to interests-gradients-drawing data. • All Communication uses interests to specify named data • Neighbor-Neighbor (Not End-to-End) • No routers, governed by task specificity • No Need for globally unique identifiers
Is It Routing ? • Kind of Reactive, Routes on Demand • No Attempt to find one loop free route • Constrained Flooding is used • Message Cache is used to avoid loops They did carry out some preliminary results
Future Research here • Target Detection Algorithm • Simulate Congestion in the network • Experiment the non-aggressive reinforcement strategy and less conservative negative reinforcements • Sensor Networks are at a stage where Internet was three decades ago
SPIN, Sensor Protocols for Information via Negotiation • Overcomes Implosion, Overlap and Resource Blindness in conventional approaches • Advocates Negotiation and Resource-adaptation
SPIN • Naming Using Meta Data • SPIN Messages ADV,REQ,DATA • Resource Management • Implementation • 3-stage handshake • Participation only when it can complete all the three stages
Performance • Compared against flooding, gossiping and ideal protocol • Metric is amount of data disseminated over time and energy consumed • SPIN-1 higher throughput than gossip but same as flooding, less energy usage • SPIN-2 ideal amount of data per unit energy
Food for Thought • If Ad-hoc networks are not yet a reality, can we ever expect Sensor Networks to be deployed • Are they really required ? ANY QUESTIONS