Context-aware caching scheme (CACS) for real-time health monitoring systems

1. Context-aware caching scheme (CACS) for real-time health monitoring systems Aarti Munjal, Aravind Kalavagattu Arizona State University CSE 535: Mobile Computing Project presentation

2. Problem Statement Formally, To design a context aware caching scheme for real-time health monitoring of patients in a community setting. The system has to be scalable, with minimum time-lag for information discovery, robust in handling the network traffic and ensure high amount of accuracy.

3. Tasks involved.. • Topology • CACS • Employing Context awareness • Search & Update • Analysis • System Design • Simulation/Implementation

4. Topology • To make it scalable, we adopt a multi-tier architecture • PDAs at leaves • Patient with sensors • Server as root • Doctor • Hubs sit at intermediate levels Server H7 H8 H1 H2 H3 H4 H5 H6 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 Figure 6: Multi-tier architecture

5. Context Aware Caching Scheme (CACS) • Aim: • To ensure data availability even in case of disconnections and failures. • Cache Resolution: Data request aimed to be solved at the highest level possible. • Query should be served by the top-level hubs with out going to the patient PDAs always. • Cache Management: Decision regarding purging less important data to make room for the critical information. • In case of overflow in traffic, critical data needs to be stored as compared to less critical ones

6. Data Structures Used for Caching • Path • Hub sequence is stored to reach the patient PDA

7. Employing Context-awareness • Context: • Environmental Conditions • Patient’s health vulnerabilities • Range of each sensor values (if it is within the safe limit or not) • Eg: Temperature of 98-99 F is safe, but we need attention if it crosses beyond • Context parameters • Priority = f(v,m,e) [used for admission control at hub level] • TTL = g(v,m,e) [used to make sure the values get refreshed timely] where, • Defined at the PDA level. • v = variance of data values • m = mobility of PDAs (patients) • e = environmental factor

8. Search and Update • Search: Request (pid,sid,path) from Server level reaches the last hub in path. do { go to immediate parent hub; broadcast to the child hubs; } while (entry_not_found) • Update: Register Packet from pda (with ret = 1) is sent to hub. Hub adds the entry in its data table, appends its own id in ‘path’ field and forwards the packet to next-level hub. • Packet is forwarded until it reaches the server. Server H7 H8 H1 H2 H3 H4 H5 H6 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 Figure: Multi-tiers

9. Analysis: Comparison with Simple Caching Scheme • Performance Measures: • Average cost for search and update • Request Satisfaction factor • Parameters for Evaluation • N = Total No. of Nodes • n = No. of levels • r = Branching Factor • p = Probability that each hub has data • λr = Request Generation Rate • λ = PDA Mobility Rate • c = Average No. of levels for broadcast • a = Probability that path to PDA is known

10. Analysis Contd… • Average Cost Function for CACS: C = λc[(1-p)n-1{an+(1-a)(c+ r-1)} + (1-(1-p)n)(n-1)/2] + λm(n) • Average Cost Function for Simple Caching Scheme: C = λc[(1-p){an + (1-a)(N-1)/2}] + λm(n)

11. Analysis contd… • Search cost: λc[(1-p)n-1{an+(1-a)(c+ r-1)} + (1-(1-p)n)(n-1)/2] • (1-p)n-1 - probability that none of IM hubs has data • n - no of hops travelled if path to pda is known (probability a) • o/w we search path by broadcasting (probabilty (1-a)) • 1- (1-p)n - probability that at least one of the IM hubs has data • (n-1)/2 - # of hops to travel on an average • Update cost: λm(n)

12. Results

13. Simulation • Simulation tool: Network Simulator (Ns2) • Simulation in Ns2 is agent-based, where agents communicate with each other through message-passing. • Three Agents: • Pda Agent (lowest level) • Hub Agent (Intermediate levels) • Server Agent (Highest level) • Two types of packets: • Request packet • Data packet

14. Simulation contd… • Storage • Tables • Communication • Packet Structure • Timer Events (TTL-based) • PDA: Refreshes data and sends to hub • Hub: Request sent to PDA • Timer & Values hashed using <pid,sid> pairs

15. Tasks: accomplished • Mathematical analysis of CACS • Its comparison with the traditional simple caching scheme • Proved: CACS performs much better than the traditional caching scheme. • Implemented the design of system for simulation • Created three agents • Data Structures used to store data at each level • Timers to refresh TTL • Incorporating Context-awareness using rules • Data admission control based on priority

16. Future Work • Request Satisfaction Factor (rs) • Number of requests satisfied/ Number of requests generated • Simple Caching Scheme: • Data stored using FCFS. • CACS: • Critical data always given preference. • rs for CACS > rs for Simple Caching Scheme • Due to the context-aware caching: stores most frequently asked or critical data all the time. • Simulating the system for a large community of patients for testing and validating the mathematical analysis.

17. References • Krishna Venkatasubramanian, Guofeng Deng, Tridib Mukherjee, John Quintero, Valliappan Annamalai and S. K. S. Gupta, Ayushman: A Wireless Sensor Network Based Health Monitoring Infrastructure and Testbed, IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS), 2005 • Y. Du and S. K. S. Gupta, COOP - A cooperative caching service in MANETs, In Proc. of ICAS-ICNS 2005. Joint International Conference on, Tahiti, French Polynesia, pp 58-63, Oct. 23-28, 2005 • Anurag Kahol, Sumit Khurana, Sandeep K.S. Gupta, and Pradip K. Srimani, A Strategy to Manage Cache Consistency in a Disconnected Distributed Environment, IEEE Transactions On Parallel And Distributed Systems, VOL. 12, NO. 7, JULY 2001 • A. Skordylis, N. Trigoni and A. Guitton, A Study of Approximate Data Management Techniques for Sensor Networks, Proc of the 4th Workshop on Intelligent Solutions in Embedded Systems, 2006. • Guanling Chen and David Kotz. A Survey of Context-Aware Mobile Computing Research, Department of Computer Science, Dartmouth College, Dartmouth Computer Science Technical Report TR2000-381