1. Infocom’07 Authors:Liqian Luo, Chengdu Huang, Tarek Abdelzaher John Stankovic Presented By Rohini Kurkal Under Guidance of Dr.Bin Tang

2. Contents Introduction System Design Implementation Performance Evaluation Possible Extensions

3. Introduction Applications: -Environmental monitoring/data logging No real time communication b/w sensor and sink Disconnected system EnviroStore - cooperative storage system for sensor networks suitable for disconnected operation It is storage-centric rather than communication-centric Major concern -maximizing effective storage capacity Implemented in nesC for TinyOS and evaluated in TOSSIM

4. Storage centric paradigm  Should be simple and lightweight  Micaz has only an 8MHz 8-bit processor and a 4KB RAM,  Iris has 8KB RAM, 512KB Measurement Flash Memory  Sensor nodes do not maintain files but just writes data to collection station and never read the data they write  Data redistribution–must improve overall storage utilization

5. System Design Sink – process that runs on a user’s PC, identified by a regular IP address and a well known TCP port Data mule-collects data wirelessly from encountered nodes and dumps these data later to the base station Two types of data mules: - Intentionally relay data b/w the sink and the sensor nodes - Opportunistic data upload

6. System Model

7. System Design Data redistribution is used to maximize the effective storage space of the sensor network In-network Data Redistribution: Sensor nodes are in a single network Overloaded nodes offload data to neighboring empty nodes Cross-partition Data Redistribution: Disconnected network Overloaded nodes upload to data mules Data Mules offload to under-loaded nodes

8. In-network data redistribution Uses lazy-offload scheme to save energy – postpones data balancing until the storage overflows Overloaded nodes should satisfy below conditions: R i R imbalance Where, R i = Remaining Storage size R TH = Threshold to delay data transfer R imbalance = Parameter to allow local imbalances R i ’ = Average remaining storage

9. Contd.. Bad Idea:  Selecting neighbor with largest remaining free space  This can cause data ping-pong Prevent data ping pong - bound the amount of data transfer Remaining storage & remaining node energy must be checked Node should not invoke or accept data redistribution unless its estimated energy lifetime > estimated storage lifetime

10. Cross-partition data redistribution Uses data mules Discriminate nodes (overloaded and under-loaded):  Data mule calculates its free storage value R’m as the weighted sum αR ’ +(1-α)R m. α = 1 : mule favors redistribution to neighborhood α =0 : emphasizes upload Conserve power and reduce message collision, nodes use back-off timers

11. Transition state of sensor node

12. System Architecture of sensor nodes

13. Implementation Implemented using nesC in Tinyos Local storage space of nodes is organized into a circular buffers Uses:  It consumes minimum code and data memory  organizes space as continuous data chunk  eliminates the need for free space management mechanisms  prolongs flash lifetime by balancing write access to different locations

14. Log Files Log-array file :  Simultaneously written by different nodes  Generates a sequence of log items  Logs attributes of environmental events independently monitored by multiple nodes Log-sequence file:  one writer at a time  Multiple nodes must coordinate with each other  Maintains unique & continuous serial numbers  Used in EnviroSuite

15. Log-Array File

16. Log-Sequence File

17. PerformanceEvaluation Basic deployment configuration: field of 80 × 80 ft 2, 36 nodes were deployed Two Scenarios: Scenarios 1: Single Disconnected sensor network Scenario 2 :Partitioned sensor network with data mules

19. Comparison of data storing rate at different time

20. Why EnviroStore is different ? Used for disconnected sensor networks Extra constraint of limited energy – use lazy offload Resource limitation of individual nodes Load balancing must be dependent only on local information Has additional challenge of redistributing data between entities that are disconnected

21. Possible Extensions use of controllable data mules to optimize data redistribution and upload data replacement policies to maximize the total amount of information instead of just the amount of stored data performance evaluation of EnviroStore on real hardware platform

22. THANK YOU