Middleware For Wireless Sensor Networks Research Articles

A Model-Based Approach for Adaptable Middleware Evolution in WSN Platforms

Advances in technology call for a parallel evolution in the software. New techniques are needed to support this dynamism, to track and guide its evolution process. This applies especially in the field of embedded systems, and certainly in Wireless Sensor Networks (WSNs), where hardware platforms and software environments change very quickly. Commonly, operating systems play a key role in the development process of any application. The most used operating system in WSNs is TinyOS, currently at its TinyOS 2.1.2 version. The evolution from TinyOS 1.x and TinyOS 2.x made the applications developed on TinyOS 1.x obsolete. In other words, these applications are not compatible out-of-the-box with TinyOS 2.x and require a porting action. In this paper, we discuss on the porting of embedded system (i.e., Wireless Sensor Networks) applications in response to operating systems’ evolution. In particular, using a model-based approach, we report the porting we did of Agilla, a Mobile-Agent Middleware (MAMW) for WSNs, on TinyOS 2.x, which we refer to as Agilla 2. We also provide a comparative analysis about the characteristics of Agilla 2 versus Agilla. The proposed Agilla 2 is compatible with TinyOS 2.x, has full capabilities and provides new features, as shown by the maintainability and performance measurement presented in this paper. An additional valuable result is the architectural modeling of Agilla and Agilla 2, missing before, which extends its documentation and improves its maintainability.

Mode-oriented hybrid programming of sensor network nodes for supporting rapid and flexible utility assembly

A number of utility programs (utilities for short) have been developed to fulfill application requirements and to assist user operations such as deployment validation and fault diagnosis throughout the lifespan of wireless sensor networks (WSNs). Because these utilities exhibit diverse behaviors and are required to be loaded at various stages, utility integration is a non-trivial task for developers. To support the rapid and flexible assembly of utilities into sensor node firmware, we formulate the utility management problem as a mode-scheduling procedure, in which utilities are grouped into multiple modes and the sensor node switches between modes to run only the corresponding utilities to address application and user needs. The key contribution of this article is a novel mode-oriented programming model, in which code is organized around modes and modules for the clear abstraction of the mode-scheduling procedure. To facilitate utility assembly, the proposed model supports hybrid programming, i.e., simple declarative configuration descriptions can be used to specify the mode-scheduling logic and to load the utility modules implemented with general-purpose imperative languages. To improve system flexibility, the developer’s descriptions are compiled into a compact configuration profile that will be used by a mode scheduler embedded in a WSN operating system to automatically control the mode scheduling. We have developed a Draft platform to support the proposed programming model, including a development environment and WSN middleware implementing the mode scheduler. Our evaluation results show that Draft achieves reduced development complexity and node reconfiguration cost.

A Highly Accurate Deep Learning Based Approach for Developing Wireless Sensor Network Middleware

Despite the popularity of wireless sensor networks (WSNs) in a wide range of applications, security problems associated with them have not been completely resolved. Middleware is generally introduced as an intermediate layer between WSNs and the end user to resolve some limitations, but most of the existing middleware is unable to protect data from malicious and unknown attacks during transmission. This paper introduces a secure wireless sensor network middleware (SWSNM) based on an unsupervised learning technique called generative adversarial network algorithm. SWSNM consists of two networks: a generator (G) network and a discriminator (D) network. The G creates fake data that are similar to the real sample and combines it with real data from the sensors to confuse the attacker. The D contains multi-layers that have the ability to differentiate between real and fake data. The output intended for this algorithm shows an actual interpretation of the data that is securely communicated through the WSN. The framework is implemented in Python with experiments performed using Keras. Results illustrate that SWSNM algorithm improves the accuracy of the data and enhances its security by protecting data from adversaries. In addition, the SWSNM algorithm consumes significantly less energy, has higher throughput, and lower end-to-end delay when compared with a similar conventional approach.

Performance and Challenges of Service-Oriented Architecture for Wireless Sensor Networks.

Wireless Sensor Networks (WSNs) have become essential components for a variety of environmental, surveillance, military, traffic control, and healthcare applications. These applications face critical challenges such as communication, security, power consumption, data aggregation, heterogeneities of sensor hardware, and Quality of Service (QoS) issues. Service-Oriented Architecture (SOA) is a software architecture that can be integrated with WSN applications to address those challenges. The SOA middleware bridges the gap between the high-level requirements of different applications and the hardware constraints of WSNs. This survey explores state-of-the-art approaches based on SOA and Service-Oriented Middleware (SOM) architecture that provide solutions for WSN challenges. The categories of this paper are based on approaches of SOA with and without middleware for WSNs. Additionally, features of SOA and middleware architectures for WSNs are compared to achieve more robust and efficient network performance. Design issues of SOA middleware for WSNs and its characteristics are also highlighted. The paper concludes with future research directions in SOM architecture to meet all requirements of emerging application of WSNs.

MidSHM: A Middleware for WSN-based SHM Application using Service-Oriented Architecture

Wireless sensor network (WSN) has been used for structural health monitoring (SHM) application for a long time. However, SHM domain experts lack the knowledge of low-level network issues and cannot develop an application with high efficiency. Middleware hides low-level network and hardware related issues by providing programming abstractions for an application developer which makes it easier to develop an application. In this paper, we survey different middleware approaches and propose MidSHM, a middleware for WSN-based SHM applications using the service-oriented architecture (SOA). SOA uses loosely coupled services that can be reused flexibly to develop different applications. MidSHM is a three-layered middleware with each of the layers containing various services that address issues such as in-network processing, fault tolerance, dynamicity, quality of service etc. We describe operations of various services and use two application examples to illustrate the usability and flexibility of MidSHM. We also compare MidSHM with other SOA-based WSN middleware.

RAMSES: A new reference architecture for self-adaptive middleware in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) consist of networks composed of tiny devices equipped with sensing, processing, storage, and wireless communication capabilities. WSN nodes have limited computing resources and are usually powered by batteries. First generations of WSNs were designed to attend requirements of a unique target application usually with a single user, who was also the infrastructure owner. However, the rapid evolution in this area and the increasing of the complexity of the sensors and applications pose new challenges to WSN solutions, which can be addressed by specific middleware platforms for these networks. Existing middleware systems provide suitable mechanisms to define the high-level application logic and to deal with heterogeneity and distribution issues of WSN, but most of them do not provide explicit mechanisms to define the underlying autonomic behavior of the system, an essential feature of this kind of network. In this perspective, Autonomic Computing (AC) appears as a promising option to meet autonomic requirements in WSN middleware design. This paper presents the consolidated specification of RAMSES, a reference architecture of a self-adaptive middleware for WSNs. RAMSES was conceived in light of a well-stablished Reference Architecture Model, the RAModel. It follows the autonomic computing model MAPE-K, and presents a mapping of AC conceptual model to a set of software components. We claim that, with the aid of a middleware that supports the autonomic computing principles, a WSN becomes an autonomous WSN by design. RAMSES realizes our vision by providing: (i) an architectural template with core aspects of the self-adaptive systems from which is possible to build concrete middleware instances for self-adaptive WSNs, and (ii) a specification of the reference architecture using a formal architecture description language (Pi-ADL), which enables the representation of dynamic software architectures as required by WSNs. A scenario-based qualitative analysis and a checklist survey conducted with experts demonstrate the effectiveness of RAMSES. Moreover, a concrete WSN middleware instance derived from RAMSES was implemented as a proof of concept.

Architecting Publish/Subscribe-Based Middleware for Wireless Sensor Networks

Middleware for wireless sensor networks (WSNs) can help bridge the gap and remove impediments. Publish/Subscribe (P/S) is an asynchronous communication paradigm that supports many-to-many interactions between a set of clients. P/S paradigm is a suitable paradigm for WSNs middleware. This paper designs PSWSN, a WSNs middleware, whose architecture is composed of service management, P/S support and access management. Service management is an information publishing platform based on B/S mode, its main function is to abstract the various business functions into services. P/S support in PSWSN is a core and supports publishing and matching services. Access management is employed so that WSNs can be abstracted and accessed as logical rather than individual physical entities.

Study on the Influence of Energy Saving Control System for Intelligent Building Based on Internet of Things Technology

This article has conducted the research and analysis to the monitoring and management platform technology for existing building energy consumption equipment, and combined with the key technologies of the Internet of things technology-designed a set of intelligent system for building energy consumption monitoring and management based on wireless sensor network middle-ware. The system achieve the building energy consumption monitoring and rational utilization based on building energy service equipment (such as in lighting equipment, air conditioning equipment etc.) monitoring and management. Energy consumption of the equipment meet the scene of the user for the comfortable environment by change the state of environment , and the user can monitor the running status of all the equipment and environment variable information in the process, and to control energy consumption equipment.

Reconfigurable Publish/Subscribe Middleware for Wireless Sensor Networks

This paper presented a approach, called LBS, for modeling and implementing the architecture of wireless sensor networks (WSNs) publish/subscribe (Pub/Sub) applications using a local broker subcomponent (LBS) model. Considering the reconfigurability of WSNs applications which was necessary for WSNs middleware, a graph oriented local broker subcomponent (GOLBS) model was defined based on the LBS model by integrated WSNs middleware with Pub/Sub. The analysis indicated that GOLBS provided reconfiguration management and non-predefined dynamic reconfiguration management for WSNs middleware. The results imply that GOLBS can easily be constructed, while ensuring good reconfigurability.

Design and Implementation of Middleware for Wireless Sensor Networks

Middleware supports programming abstract which facilitate the programmer task and bridge the gap between the application and the hardware. Middleware for wireless sensor networks (WSNs) can help bridge the gap and remove impediments. This paper designs GWSN, a middleware WSNs, whose architecture is composed of runtime support, application development kits, and software development kits. Runtime support in GWSN is the core of WSNs middleware and supports executing and maintenance of WSNs applications. Application development kits includes many basic function kits, such as display editor, rule editor, and workflow editor, which support the application development of WSNs. Software development kits provides easy-to-use application programming interface.

Middleware systems for wireless sensor networks: a comparative survey

Wireless sensor networks (WSNs) play an important role of the Internet of things as one of the core technologies in ubiquitous and pervasive computing. Middleware for WSNs is a hot topic as applications and platforms in WSNs have been widely developed. This paper comparatively reviews middleware systems for WSNs. In particular, the advanced middleware systems reported recently are reviewed and all the existing middleware systems are compared in terms of important features and characteristics. First, challenging issues about the important features for designing middleware for WSNs are introduced. Then, recent advancements in middleware for WSNs are reviewed and compared.

Autonomic Wireless Sensor Networks: A Systematic Literature Review

Autonomic computing (AC) is a promising approach to meet basic requirements in the design of wireless sensor networks (WSNs), and its principles can be applied to efficiently manage nodes operation and optimize network resources. Middleware for WSNs supports the implementation and basic operation of such networks. In this systematic literature review (SLR) we aim to provide an overview of existing WSN middleware systems that address autonomic properties. The main goal is to identify which development approaches of AC are used for designing WSN middleware system, which allow the self-management of WSN. Another goal is finding out which interactions and behavior can be automated in WSN components. We drew the following main conclusions from the SLR results: (i) the selected studies address WSN concerns according to the self-*properties of AC, namely, self-configuration, self-healing, self-optimization, and self-protection; (ii) the selected studies use different approaches for managing the dynamic behavior of middleware systems for WSN, such as policy-based reasoning, context-based reasoning, feedback control loops, mobile agents, model transformations, and code generation. Finally, we identified a lack of comprehensive system architecture designs that support the autonomy of sensor networking.

MARINE

Wireless sensor networks (WSNs) operate in a highly heterogeneous and dynamic scenario. On one hand, there is a wide range of potential applications for WSNs, each one with different features and requirements and defining a different mission for the sensor nodes to accomplish. On the other hand, the execution context regarding the devices, networks and the physical environment around is subject to frequent changes. In order to achieve the best network performance while meeting requirements of different application missions and contexts, it is crucial to endow the WSN with customization and adaptation capabilities. Such capabilities should be preferably provided by a middleware layer that translates application missions to network configuration in a transparent way for the final users and client applications. This middleware should also provide facilities to program the WSN nodes, to access sensor generated data and to promote interoperability among different applications and networks. To tackle these challenges, we propose MARINE (MiddlewAre for Resource and mIssion-oriented sensor NEtworks), a WSN middleware built on REST and microkernel architectural patterns. MARINE tailors the WSN to requirements of each application mission while saving the overall resource consumption in sensor nodes.

Dynamic Data Storage Estimation for Multiple Concurrent Applications Using Probability Distribution Modeling in WSNs

Wireless sensor networks (WSN) have become a mainstream technology for environmental monitoring and observing various variables of interest over extended periods of time via large-scale networks of sensors. WSNs have a wide range of applications including wildfire detection, healthcare, military, and habitat monitoring. In all such application areas, gathering and then relaying captured data to a central unit is often considered the primary task of the network. Scientific analysis however often requires WSNs to capture and store variables for long periods of time. Storing and managing flows of data tend to be challenging issues because WSNs often consist of nodes with limited processing, memory, and power resources. Therefore the software layer in WSNs needs to implement an efficient data storage allocation mechanism in order to provide sufficient memory space for multiple applications. In this paper we propose a novel statistical approach for estimating applications storage requirements. Our proposed mechanism has been originally developed and implemented in a new WSN middleware called Sensomax, which is an agent-based decentralized middleware with multiple concurrent applications support for dynamic data gathering in WSNs. The mechanism described here proved to be an effective technique for proactively allocating memory to multiple applications with different operational paradigms.

Interconnection between IP Networks and Wireless Sensor Networks

With applications ranging from environmental and health monitoring to military surveillance and inventory tracking, wireless sensor networks (WSNs) are changing the way we collect and use data and will be a major part of our technological future. The decreased manufacturing cost of these small devices has made it reasonable to deploy many sensor nodes—tens to thousands and more—over large and small indoor and outdoor areas for sensing tasks. With this increase in density data-gathering problems come. It would be useful if an IP-based host could collect information from multiple remote data-centric networks via transparent communication among sensor nodes and IP-based hosts, using a common application programming interface (API). Two APIs are presented for efficiently producing data in WSN and retrieving the data from an IP network. An associated WSN middleware layer called dynamic service is used to effectively interconnect these two APIs. These three components work together in harmony to enable IP-based hosts to gather sensed data from one or more remote WSNs through application-layer gateways which provide seamless interconnection between different remote WSNs and the IP network.

REED: Flexible rule based programming of wireless sensor networks at runtime

Wireless Sensor Networks (WSNs) have emerged as an enabling technology for a variety of distributed applications. WSN middleware eases the development of these applications by providing a uniform programming environment. In this paper we present a rule based approach called REED (Rule Execution and Event Distribution) and describe how it supports flexible programming of WSNs at runtime. Indeed REED is required by the nature of its project setting to allow runtime programming. We demonstrate that by combining this runtime programmability with rules in an event, condition, action format we can support a range of paradigms, including Publish-subscribe and data aggregation algorithms. Current WSN middleware solutions have limited on-line programmability support so the applications cannot re-configure their WSNs while operational. Yet the runtime nature of the prototype requires both the distribution of rules and the events that trigger them so we also describe the rule management approach used to support the rule distribution; in particular a novel rule merging and filtering algorithm is described. The paper reports on the results gained from a REED prototype system constructed in our laboratory using Gumstix.

Experimental Performance Evaluation of POBICOS Middleware for Wireless Sensor Networks

The advances in the theory of wireless sensor networks have been remarkable during the past decades, but there is a lack of extensive experimental evaluations. In this paper we present performance-evaluation methods and results for POBICOS (platform for opportunistic behaviour in incompletely specified, heterogeneous object communities), which is an advanced middleware for wireless sensor networks (WSNs). The measurements concern energy consumption, duty cycle, and OS task profiling as well as communication characteristics such as round trip time (RTT) and throughput. In addition, a bandwidth analysis during a long-term experiment of fully functional POBICOS network and application is studied. Based on the evaluation results, power mode and data cache improvements are presented as well as CPU clock frequency optimizations.

Middleware for wireless sensor networks: an outlook

Abstract In modern distributed computing, applications are rarely built directly atop operating system facilities, e.g., sockets. Higher-level middleware abstractions and systems are often employed to simplify the programmer’s chore or to achieve interoperability. In contrast, real-world wireless sensor network (WSN) applications are almost always developed by relying directly on the operating system. Why is this the case? Does it make sense to include a middleware layer in the design of WSNs? And, if so, is it the same kind of software system as in traditional distributed computing? What are the fundamental concepts, reasonable assumptions, and key criteria guiding its design? What are the main open research challenges, and the potential pitfalls? Most importantly, is it worth pursuing research in this field? This paper provides a (biased) answer to these and other research questions, preceded by a brief account on the state of the art in the field.

A Self-Adaptive Spectrum Management Middleware for Wireless Sensor Networks

The vision of the Internet of Things, wherein everyday objects are embedded with smart wireless sensor devices, is making these sensor devices increasingly pervasive. As the density of their deployment in overlapping or adjacent areas increases, the contention for the unlicensed 2.4GHz ISM band will also increase. To deal with the crowded spectrum, nodes must use the channels more judiciously and be able to adapt by detecting and switching to the most available channel. The SAS middleware that we have developed, is a self-adaptive spectrum management middleware for wireless sensor networks that enhances single-frequency MAC protocols with multi-frequency capability, without any change in hardware. It allows a single-frequency MAC protocol, like B-MAC, to automatically adapt to the least congested physical channel at runtime. SAS supports a combination of receiver-initiated and sender-initiated schemes to decide when to switch the channel and which channel to switch to. We have implemented the B-MAC protocol integrated with SAS in TinyOS 2.1 on TelosB sensor devices and evaluated its performance on the conditions of varied data flows and the interference produced by a jammer. The results demonstrate that the integrated B-MAC protocol outperforms B-MAC in terms of packet reception ratio, system throughput, average packet delay, and energy consumption.

Study on the Context-Aware Middleware for Ubiquitous Greenhouses Using Wireless Sensor Networks

Wireless Sensor Network (WSN) technology is one of the important technologies to implement the ubiquitous society, and it could increase productivity of agricultural and livestock products, and secure transparency of distribution channels if such a WSN technology were successfully applied to the agricultural sector. Middleware, which can connect WSN hardware, applications, and enterprise systems, is required to construct ubiquitous agriculture environment combining WSN technology with agricultural sector applications, but there have been insufficient studies in the field of WSN middleware in the agricultural environment, compared to other industries. This paper proposes a context-aware middleware to efficiently process data collected from ubiquitous greenhouses by applying WSN technology and used to implement combined services through organic connectivity of data. The proposed middleware abstracts heterogeneous sensor nodes to integrate different forms of data, and provides intelligent context-aware, event service, and filtering functions to maximize operability and scalability of the middleware. To evaluate the performance of the middleware, an integrated management system for ubiquitous greenhouses was implemented by applying the proposed middleware to an existing greenhouse, and it was tested by measuring the level of load through CPU usage and the response time for users’ requests when the system is working.