Elsevier

Information Sciences

Volume 222, 10 February 2013, Pages 113-125
Information Sciences

A store-carry-process-and-forward paradigm for intelligent sensor grids

https://doi.org/10.1016/j.ins.2012.08.016Get rights and content

Abstract

Store-carry-and-forward DTN (Delay/Disruption Tolerant Networking) protocols offer new possibilities in scenarios where there is intermittent connectivity, asymmetric bandwidths, long and variable latency and ambiguous mobility patterns. In this article we propose a new paradigm – store-carry-process-and-forward – based on mobile code to improve the integration of wireless sensor networks and grid computing infrastructures. We describe the implementation of a delay tolerant grid service, the computer element, to give computing access to an intermittently connected wireless sensor network. The result is an intelligent system which adapts dynamically to intermittent disconnections and improves multi-application coexistence. Finally, we present as an example a real case application which provides general purpose grid access to a multi-application mobile robot node sensor network.

Introduction

Grid computing [33], [15] has consolidated as a technology capable of solving some of the most challenging scientific projects of our century. The needs of these projects usually include complex computation of data obtained from different sources and stored in large storage resources. The main goal of grid computing, precisely, is to share these resources among different institutes and virtual organizations across high-speed networks and distribute and coordinate its processing.

Wireless sensor networks (WSNs), on the other hand, is a technology that can be very useful when it comes to acquiring and transporting data collected in widely spaced areas. These networks consist of different nodes carrying different sensors along with autonomous computational devices which transmit data through the network to some specific locations or data sinks.

This article analyzes how both technologies, grid computing and wireless sensor networks, can be combined into an integrated WSNs and computer grid infrastructure allowing new functionalities. The corner stone of this conjugation is using delay and disruption tolerant networking (DTN) concepts [14] along with mobile code to create an intelligent grid network capable of routing and managing processes depending on the context. Some other recent proposals, which will be further described in Section 2, integrate WSNs and grid computing, as well. However, our proposal comes from the network perspective. We consider WSNs nodes as intermittent connected nodes, containing asymmetric bandwidths, long and variable latencies and ambiguous mobility patterns. This new perspective contributes to the creation of a novel concept of intelligent grid computing networks, going beyond the possibilities of the reviewed literature in some current scenarios, and providing promising prospects for supporting future grid services.

The routing decision making and execution policies travel with the messages, instead of being static and exactly the same for all nodes. These policies, in the shape of mobile code, can take into account the context of the nodes to choose the behavior that fits best in each situation. All in all, the system acts more like an ant colony, with differentiated autonomous parts acting locally but with a cooperative aim, rather than a traditional and more inflexible system. Thus, using mobile code makes the grid network an intelligent system, pliable enough to adapt to new scenarios of grid computing. However, the proposed system cannot be considered a silver bullet for all grid computing; in highly connected grids, with low latencies and where data does not need to be processed before getting to the execution destination, mobile code would introduce an unnecessary extra overhead and other unwanted side effects.

The original contributions of this paper are: a grid computing model based on mobile code to allow intermittently connected wireless sensor networks to seamlessly coexist with other traditional connected services and a grid computer service which transparently gives access to a general purpose multi-application mobile robot node sensor network.

This paper is organized as follows: Section 2 is a state of the art of the combined use of grid computing and wireless sensor networks, having a closer look at those ones which suffer from intermittent connections and those using mobile code. Section 3 presents our proposal, an intelligent system following the store-carry-process-and-forward paradigm. In Section 4 we present a delay tolerant architecture for grid services which are transiently unavailable. In Section 5 we analyze how to include intermittent connected networks in traditional grid computing systems using mobile code. Services such as computing, storage, information service and monitoring will be discussed in detail. Finally, Section 6 presents the conclusions we have come to.

Section snippets

Background

There are several efforts already published on the integration of wireless sensor networks and grid computing. Studies like [30] and [23] propose different ways of extending the computing grid paradigm to allow the integration of wireless sensor networks and grid computing infrastructures. This section analyzes the state of the art of other technologies: mobile code and DTN protocols which we believe can extend and improve this integration. In Fig. 1, research overlapping of the four

Integrating delay/disruption tolerant WSNs in grid computer infrastructures using mobile code

In this section we propose a way to integrate intermittently connected WSNs in computer grid infrastructures. On one hand, the data acquired by the WSNs can be processed and stored using traditional grid services inside connected regions. On the other hand, and a more challenging option, sensors can be considered as grid sources of data commanded by the very grid users themselves. We propose the job behavior that evolves beyond the traditional read-process-and-storage model – that is reading

Implementation

The execution environments on which intelligent messages run are called platforms. We need to implement on every sensor grid node an execution environment platform to let intelligent messages carry grid level information to run on. In order to implement intelligent messages described in the previous sections, we need some special platforms: besides being capable of executing code, platforms must allow the code to be forwarded from one sensor node to another, stopping their code, resuming its

A practical example: a general purpose grid multi-application robot sensor network

In this section we present as an example of our proposal, a way to include a general purpose multi-application mobile node sensor network in an existing computer grid infrastructure.

We have implemented a computer element job manager which transparently gives grid access to a robot wireless sensor network. This job manager creates an intelligent message for every grid job submitted. Users using gLite’s job description language [20] choose among three different types of intelligent message

Conclusions and future work

We have presented in this paper an intelligent system to transparently integrate intermittently connected wireless sensor networks to computing grid infrastructures. We have presented a new paradigm called store-carry-process-and-forward, which proposes how to process data while the information is stored, waiting for the DTN information to be forwarded.

From another hand, as a practical example of our proposal, we have introduced a computer element service which provides access to a general

Acknowledgements

Carlos Borrego and Sergi Robles gratefully acknowledge the support from Ministerio de Ciencia e Innovación, Spain. This work was supported in part by Grants TIN2010-15764, FPA2007-66152-C02-00, TIN2010-15764, FPA2010-21919-C03-02 and FPA2007-66708-C03-02 from Ministerio de Ciencia e Innovación, Spain.

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