Middleware Technologies for Cloud of Things - a survey

The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017

Middleware Technologies for Cloud of Things - a survey

The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017

A study of publish/subscribe systems for real-time grid monitoring

Monitoring and controlling a large number of geographically distributed scientific instruments is a challenging task. Some operations on these instruments require real-time (or quasi real-time) response which make it even more difficult. In this paper, we describe the requirements of distributed monitoring for a possible future electrical power grid based on real-time extensions to grid computing. We examine several standards and publish/subscribe middleware candidates, some of which were specially designed and developed for grid monitoring. We analyze their architecture and functionality, and discuss the advantages and disadvantages. We report on a series of tests to measure their real-time performance and scalability

AstroGrid-D: Grid Technology for Astronomical Science

We present status and results of AstroGrid-D, a joint effort of astrophysicists and computer scientists to employ grid technology for scientific applications. AstroGrid-D provides access to a network of distributed machines with a set of commands as well as software interfaces. It allows simple use of computer and storage facilities and to schedule or monitor compute tasks and data management. It is based on the Globus Toolkit middleware (GT4). Chapter 1 describes the context which led to the demand for advanced software solutions in Astrophysics, and we state the goals of the project. We then present characteristic astrophysical applications that have been implemented on AstroGrid-D in chapter 2. We describe simulations of different complexity, compute-intensive calculations running on multiple sites, and advanced applications for specific scientific purposes, such as a connection to robotic telescopes. We can show from these examples how grid execution improves e.g. the scientific workflow. Chapter 3 explains the software tools and services that we adapted or newly developed. Section 3.1 is focused on the administrative aspects of the infrastructure, to manage users and monitor activity. Section 3.2 characterises the central components of our architecture: The AstroGrid-D information service to collect and store metadata, a file management system, the data management system, and a job manager for automatic submission of compute tasks. We summarise the successfully established infrastructure in chapter 4, concluding with our future plans to establish AstroGrid-D as a platform of modern e-Astronomy.Comment: 14 pages, 12 figures Subjects: data analysis, image processing, robotic telescopes, simulations, grid. Accepted for publication in New Astronom

A Generic Development and Deployment Framework for Cloud Computing and Distributed Applications

Cloud computing have paved the way for advance of IT-based demand services. This technology helps decrease operation costs, solve scalability issue and many more user and provider constraints. However, development and deployment of distributed applications on cloud environment becomes a more and more complex tasks. Cloud users must spend a lot of time to prepare, install and configure their applications on clouds. In addition, after development and deployment, the applications almost cannot move from a cloud to others due to the lack of interoperability between them. To address these problems, we present in this paper a novel development and deployment framework for cloud distributed applications/services. Our approach is based on abstraction and object-oriented programming technique, allowing users to easily and rapidly develop and deploy their services into cloud environment. The approach also enables service migration and interoperability among the clouds

Grid Interoperation with ARC Middleware for the CMS Experiment

The Compact Muon Solenoid (CMS) is one of the general purpose experiments at the CERN Large Hadron Collider (LHC). CMS computing relies on different grid infrastructures to provide computational and storage resources. The major grid middleware stacks used for CMS computing are gLite, Open Science Grid (OSG) and ARC (Advanced Resource Connector). Helsinki Institute of Physics (HIP) hosts one of the Tier-2 centers for CMS computing. CMS Tier-2 centers operate software systems for data transfers (PhEDEx), Monte Carlo production (ProdAgent) and data analysis (CRAB). In order to provide the Tier-2 services for CMS, HIP uses tools and components from both ARC and gLite grid middleware stacks. Interoperation between grid systems is a challenging problem and HIP uses two different solutions to provide the needed services. The first solution is based on gLite-ARC grid level interoperability. This allows to use ARC resources in CMS without modifying the CMS application software. The second solution is based on developing specific ARC plugins in CMS software

SOMM: A New Service Oriented Middleware for Generic Wireless Multimedia Sensor Networks Based on Code Mobility

Although much research in the area of Wireless Multimedia Sensor Networks (WMSNs) has been done in recent years, the programming of sensor nodes is still time-consuming and tedious. It requires expertise in low-level programming, mainly because of the use of resource constrained hardware and also the low level API provided by current operating systems. The code of the resulting systems has typically no clear separation between application and system logic. This minimizes the possibility of reusing code and often leads to the necessity of major changes when the underlying platform is changed. In this paper, we present a service oriented middleware named SOMM to support application development for WMSNs. The main goal of SOMM is to enable the development of modifiable and scalable WMSN applications. A network which uses the SOMM is capable of providing multiple services to multiple clients at the same time with the specified Quality of Service (QoS). SOMM uses a virtual machine with the ability to support mobile agents. Services in SOMM are provided by mobile agents and SOMM also provides a t space on each node which agents can use to communicate with each other