IHP Im Technologiepark Frankfurt (Oder) Germany IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved tinyDSM: A Highly Reliable Cooperative Data Storage For Wireless Sensor Networks Krzysztof Piotrowski, Peter Langendörfer, Steffen Peter

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved Outline Motivation Goals Our solution Future work Conclusions

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved Motivation Wireless Sensor Network is a loosely coupled multiprocessor system limitations - energy – trade-off between activity and lifetime - network – transmission losses, delays, network dynamics - computational power – adds to both above mentioned great number of nodes Cooperation in WSN is the way to success! Cooperation is data exchange!

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved Motivation, cont. The Environment The size of the network is not limited -The data is locality bound Nodes appear and disappear -Nodes represent a medium for the data Cooperation based on data exchange in a common storage -Replication increases the reliability -Historical data increases the usability Need for mechanisms to exchange and store the data in a reliable way!

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved Loosely coupled multiprocessors - not easy to program - memory consistency problems Distributed Shared Memory Introduces an additional layer to loosely coupled multiprocessors + hides the complexity + cares about memory consistency Consistency / performance trade-off Motivation, cont. CPU MEMORY CPU MEMORY COMMON MEMORY

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved Goals A reliable data storage middleware Distributing the data items - availability - cooperative access - consistency of the replicas - historical data - event detection Security Configurable

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved The solution – the idea At start-up each node announces own shared variables The neighbours decide on a random basis to replicate it Changes to a shared variable are sent to the neighbours On update the new value is checked if any event occurred Every node having a replica can provide the data

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved The solution – addressing There is one global set of variables per application defines the shared part of the memory Each node has an address represented either by Id or location Each variable has its type defines the granularity The timestamp allows the versioning of the values allows creating history Each instance of a variable is a tuple

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved The solution – messages There are three types of request messages GET – request for reading a specific variable SET – request for writing a specific variable UPDATE – request for updating the replicas of a specific variable With or without acknowledgement (verification) Each of them is completed with an acknowledgement message ANSWER – the results for the GET request SET_ACK – indicates that the SET request was fulfilled UPDATE_ACK – indicates that an UPDATE request was fulfilled The GET and UPDATE messages are usually broadcast, all other messages are usually unicast.

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved The solution – architecture Application logic defines the sources of data and actions in case of events. Event & Replication Logic takes the decision on the replication of data, storage of new data and controls data locating. It is also responsible for detecting the events for the new data. Query Logic is responsible for interpreting incoming messages (queries) and building results into answer messages. Memory Manager controls the physical data storage on the node. Communication Interface allows communication with other nodes.

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved The solution – customization Policies control the behaviour of the system Policies chosen while defining a variable define the handling of all instances of that variable in the system - the requested consistency - the replication strategy - the used storage space, size of the history, etc. Policies can control the behaviour in case of an event - diverse strategies to avoid false positives and false negatives Policies allow for tuning the application - exchanging the policy file allows to create several versions of the application with different requirements using the same source code

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved The solution – preliminary evaluation 20 x 20 nodes network (regular grid) Several combinations of network parameters One defined variable Variable set once every five seconds Ten updates + up to five verifications (quality parameter) 25% replication probability (quantity parameter) Network name Replication range (hops) Radio rangeNumber of replicas Network1112 Network2126 Network3216

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved The solution – preliminary evaluation, cont.

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved The solution – preliminary evaluation, cont.

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved The solution – preliminary evaluation, cont.

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved The solution – preliminary evaluation, cont.

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved Future work Definition of deployment scenarios for simulations additional simulations have to be done for several scenarios Definition and simulation the system parameters and mechanisms have to be defined and evaluated regarding the introduced costs and performance features Application programming tools have to be developed in order to make the use of the approach easier Moving the model to real Wireless Sensor Network verification of the model on real nodes potential hardware-software functionality shifts

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved Future improvements Database abstraction layer allows accessing the data stored in the WSN like a database Distributed Event processing in case an event is detected it can be validated within the network Single system image version in smaller networks complete replication may be possible Global variables and ownership migration global variables are defined per network not per node to avoid access problems in case the owning node is lost the ownership can be transferred to another node

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved Conclusions The presented reliable distributed data storage that adapts the number of replicas to the defined number is the first step towards providing the Distributed Shared Memory to the WSN Concept of DSM was primarily used to enable parallel distributed computing on powerful devices connected via powerful network interfaces The idea fits perfectly to the WSN application area as well Providing the concept to the WSN together with its features and tools that ease its use enables many new applications in that area It allows the nodes to operate more active and autonomous from a base station by injecting more intelligence into the network.

IHP Im Technologiepark Frankfurt (Oder) Germany © All rights reserved Thank you Questions?