Telecommunication e‐services orchestration enabling business process management

840

425

The world population is growing at a rapid pace. Towns and cities are accommodating half of the world's population thereby creating tremendous pressure on every aspect of urban living. Cities are known to have large concentration of resources and facilities. Such environments attract people from rural areas. However, unprecedented attraction has now become an overwhelming issue for city governance and politics. The enormous pressure towards efficient city management has triggered various Smart City initiatives by both government and private sector businesses to invest in information and communication technologies to find sustainable solutions to the growing issues. The Internet of Things (IoT) has also gained significant attention over the past decade. IoT envisions to connect billions of sensors to the Internet and expects to use them for efficient and effective resource management in Smart Cities. Today, infrastructure, platforms and software applications are offered as services using cloud technologies. In this paper, we explore the concept of sensing as a service and how it fits with the IoT. Our objective is to investigate the concept of sensing as a service model in technological, economical and social perspectives and identify the major open challenges and issues.

Section: Environmental Managementmentioning

confidence: 99%

Sensing as a service model for smart cities supported by Internet of Things

Perera

Zaslavsky

Christen

et al. 2013

840

425

“…In this context, the integration and development of systems based on Information and Communication Technologies (ICT) and, more specifically, the Internet of Things (IoT) , are important enablers of a broad range of applications, both for industries and the general population, helping make smart cities a reality. In is researched the emergence of new business process management and of novel service‐oriented architectures focused on the development of electronic services available to customers.…”

Section: Towards the Cities Of The Futurementioning

confidence: 99%

User‐centric smart buildings for energy sustainable smart cities

Moreno

Zamora

Skarmeta

2013

Over six billion people are expected to live in cities and surrounding regions by 2050. Consequently, in the near future, the autonomic and smart operation of cities may be a critical requirement to improve the economic, social, and environmental well‐being of citizens. Smart urban technologies represent an important contribution to the sustainable development of cities, making smart cities a reality. In this sense, the energy sustainability of cities has become a global concern, bringing with it a wide range of research and technological challenges that affect many aspects of people's lives. Because most of the human lifetime is spent indoors, buildings, which make up a city subsystem, require special attention. Indeed, buildings are the cornerstone in terms of power consumption and CO2 emissions on a global scale. In this paper, we analyze the role that buildings play in terms of their energy performance at city level and present an energy‐efficient management system integrated in a building automation platform based on an Internet of Things approach. Occupants play a crucial role in the system's operation to achieve energy efficient building performance, and any impact on self‐sustainable smart cities will be a consequence of efficient user‐centric smart building designs. Our proposal represents a user‐centric smart solution as a contribution to the energy sustainability of modern cities. The building management platform has been deployed in a real (smart) building, in which a set of tests were carried out to assess different concerns involved in the building's infrastructure management. The first stages of this experiment have already resulted in an energy saving in heating of about 20% at building level, which could translate into a reduction of 8% in the energy consumption of buildings at a European city level. Copyright © 2013 John Wiley & Sons, Ltd.

“…Therefore, its use can simplify the process of traffic simulations in most of the cases in opportunistic networks including situations when we obtain non-predictable shape and scale of the traffic. The approach allows us to evaluate queuing delays, loss, availability and occupancy of the system per application or interface at different layers in accordance to TCP/IP model [52][53][54]. The proposed procedure also supports self-configuration of the distributed opportunistic network [55] and can be very useful in all cases of distributed networks with mobile objects.…”

Section: Traffic Measurement Analyses and Simulationmentioning

confidence: 99%

3G network traffic sources measurement and analysis

Goleva

Atamian

Mirtchev

et al. 2013

In this paper, we show statistical analyses of several types of traffic sources in a 3G network, namely voice, video and data sources. For each traffic source type, measurements were collected in order to, on the one hand, gain better understanding of the statistical characteristics of the sources and, on the other hand, enable forecasting traffic behaviour in the network. The latter can be used to estimate service times and quality of service parameters. The probability density function, mean, variance, mean square deviation, skewness and kurtosis of the interarrival times are estimated by Wolfram Mathematica and Crystal Ball statistical tools. Based on evaluation of packet interarrival times, we show how the gamma distribution can be used in network simulations and in evaluation of available capacity in opportunistic systems. As a result, from our analyses, shape and scale parameters of gamma distribution are generated. Data can be applied also in dynamic network configuration in order to avoid potential network congestions or overflows.