The heterogeneous cellular network (HCN) is a promising technology to handle the rising number of... more The heterogeneous cellular network (HCN) is a promising technology to handle the rising number of devices due to their universal presence. This rising popularity HCN based Machine-to-Machine (M2M) communications is opening new opportunities and also bringing forth new system design issues. However, the main challenge of M2M communication is the possibility of huge traffic and significant difference in the nature of M2M traffic than the current commercial traffic for which current cellular network is designed and optimized. In this article, we investigate the uplink resource allocation problem of M2M devices (MDs) in the multiple Femto base station's coverage. We first model the uplink power and sub-carrier allocation in femtocells independently; Based on the cooperative game resource allocation among MDs is analyzed through non-transferable utility game to enhance the data rate performance with minimum utilization of power. Simulation results show that the resource allocation mo...
Machine-to-Machine (M2M) communication has led to a new paradigm of Internet of Things (IoT). The... more Machine-to-Machine (M2M) communication has led to a new paradigm of Internet of Things (IoT). The future of M2M communication in smart home lies in the aggregation and allocation of resources and service provisioning of diverse applications using different radio technologies. M2M communication may operate on the virtual sensor network to provide independent applications running on heterogeneous network simultaneously. M2M is going to play a major role in the area of Smart Home and Ambient Assisted Living (SHAAL) providing assistance to the elderly people with smart sensors that monitor the home environment and provides aid health monitoring to human requiring medical assistance. The current state of the art frameworks are dedicated to specific applications with the support of single radio network with limited service provisioning options. However, in order to fully exploit the resources in this paper we present a service provisioning framework realization of M2M in virtual sensor n...
2015 5th National Symposium on Information Technology: Towards New Smart World (NSITNSW), 2015
Wireless Sensor Network (WSN) has led to a new paradigm of Internet of Everything (IoE). In case ... more Wireless Sensor Network (WSN) has led to a new paradigm of Internet of Everything (IoE). In case of Ambient Assisted Living (AAL) that is based on the sensor network is usually deployed for single application. However, the future of WSNs based on sensors lies in the multiple application support and the aggregation of resources either in the form of hardware or software. To deal with the challenges of aggregation of sensors in the health care environment, virtualization of a sensor network is an evolving concept that enables aggregation of multiple independent heterogeneous sensor networks under one roof. In order to virtualize the sensors and networks, middleware layer role is the most dominant one. Furthermore, middleware for sensors poses the overhead challenges like processing time, memory utilization, sampling rate, delay, and power consumption. In this paper efforts have been put forward by proposing a middleware framework for sensor network that uses multi-threading technique that increases the sampling frequency and reduces the delay caused by the hardware abstraction layer that resides on top each sensor node. Mathematical model shows significant improvement in the processing time.
Wireless Sensor Network (WSN) is leading to a new paradigm of Internet of Everything (IoE). WSNs ... more Wireless Sensor Network (WSN) is leading to a new paradigm of Internet of Everything (IoE). WSNs have a wide range of applications but are usually deployed in a particular application. However, the future of WSNs lies in the aggregation and allocation of resources, serving diverse applications. WSN virtualization by the middleware is an emerging concept that enables aggregation of multiple independent heterogeneous devices, networks, radios and software platforms; and enhancing application development. WSN virtualization, middleware can further be categorized into sensor virtualization and network virtualization. Middleware for WSN virtualization poses several challenges like efficient decoupling of networks, devices and software. In this paper efforts have been put forward to bring an overview of the previous and current middleware designs for WSN virtualization, the design goals, software architectures, abstracted services, testbeds and programming techniques. Furthermore, the paper also presents the proposed model, challenges and future opportunities for further research in the middleware designs for WSN virtualization.
2013 IEEE International Conference on Signal and Image Processing Applications, 2013
Interference Management (1M) is one of the major challenges of next generation wireless communica... more Interference Management (1M) is one of the major challenges of next generation wireless communication. Fractional Frequency Reuse (FFR) has been acknowledged as an efficient 1M technique, which offers significant capacity enhancement and improve cell edge coverage with low complexity. In literature, FFR has been analyzed mostly with cellular networks described by Hexagon Grid Model, which is neither tractable nor scalable to the dense deployment of next generation wireless networks. Moreover, the perfect geometry based grid model tends to overestimate the system performance and not able to reflect the reality. In this paper, we use the stochastic geometry approach, FFR is analyzed with cellular network modeled by homogeneous Poisson Point Process (PPP). A dynamic frequency allocation scheme is proposed which take into account the randomness of the cell coverage area describe by Voronoi tessellation. It is shown that the proposed scheme outperforms the traditional fixed frequency allocation schemes in terms of per user capacity and capacity density.
2013 IEEE Symposium on Wireless Technology & Applications (ISWTA), 2013
Machine-to-Machine (M2M) communication in cellular network is the driver for the future Internet ... more Machine-to-Machine (M2M) communication in cellular network is the driver for the future Internet of Things (IoT). The main challenge of M2M communication is the possibility of huge traffic in the uplink network that can cause problem in the network. This paper considers the problem of resource allocation among machines connecting in uplink to different femto base stations (FBSs). Resource allocation problem is analyzed through both non-cooperative and cooperative game to maximize their data rate and minimize utilization of power. Numerical result shows that by adapting non-cooperative game, all machines are getting data rate as per Nash Equilibrium (NE) or either they can set their strategy to maximize their data rate selfishly. On the other hand for coalitional game theory approach machines who participate in game are getting fair resource allocations.
Abstract: Wireless Sensor Network (WSN) is leading to a new paradigm of Internet of
Everything (I... more Abstract: Wireless Sensor Network (WSN) is leading to a new paradigm of Internet of Everything (IoE). WSNs have a wide range of applications but are usually deployed in a particular application. However, the future of WSNs lies in the aggregation and allocation of resources, serving diverse applications. WSN virtualization by the middleware is an emerging concept that enables aggregation of multiple independent heterogeneous devices, networks, radios and software platforms; and enhancing application development. WSN virtualization, middleware can further be categorized into sensor virtualization and network virtualization. Middleware for WSN virtualization poses several challenges like efficient decoupling of networks, devices and software. In this paper efforts have been put forward to bring an overview of the previous and current middleware designs for WSN virtualization, the design goals, software architectures, abstracted services, testbeds and programming techniques. Furthermore, the paper also presents the proposed model, challenges and future opportunities for further research in the middleware designs for WSN virtualization.
Machine-to-Machine (M2M) communication has led to a new paradigm of Internet of Things (IoT). The... more Machine-to-Machine (M2M) communication has led to a new paradigm of Internet of Things (IoT). The future of M2M communication in smart home lies in the aggregation and allocation of resources and service provisioning of diverse applications using different radio technologies. M2M communication may operate on the virtual sensor network to provide independent applications running on heterogeneous network simultaneously. M2M is going to play a major role in the area of Smart Home and Ambient Assisted Living (SHAAL) providing assistance to the elderly people with smart sensors that monitor the home environment and provides aid health monitoring to human requiring medical assistance. The current state of the art frameworks are dedicated to specific applications with the support of single radio network with limited service provisioning options. However, in order to fully exploit the resources in this paper we present a service provisioning framework realization of M2M in virtual sensor network for SHAAL, which allows independent parties to work together in a secure and reliable manner. In addition to this, the framework is designed to include benefits of Service Oriented Architecture (SOA) and Resource Oriented Architecture (ROA) along with the use of different low power, low data rate protocols. A middleware is used as a platform to link the underlying virtual networks with various applications. The network virtualization approach is adopted to design an efficient middleware framework that can effectively discover and manage the underlying network resources and provide services at home gateway. The framework will be used as the basis for the development of the SHAAL networked system.
The heterogeneous cellular network (HCN) is a promising technology to handle the rising number of... more The heterogeneous cellular network (HCN) is a promising technology to handle the rising number of devices due to their universal presence. This rising popularity HCN based Machine-to-Machine (M2M) communications is opening new opportunities and also bringing forth new system design issues. However, the main challenge of M2M communication is the possibility of huge traffic and significant difference in the nature of M2M traffic than the current commercial traffic for which current cellular network is designed and optimized. In this article, we investigate the uplink resource allocation problem of M2M devices (MDs) in the multiple Femto base station's coverage. We first model the uplink power and sub-carrier allocation in femtocells independently; Based on the cooperative game resource allocation among MDs is analyzed through non-transferable utility game to enhance the data rate performance with minimum utilization of power. Simulation results show that the resource allocation mo...
Machine-to-Machine (M2M) communication has led to a new paradigm of Internet of Things (IoT). The... more Machine-to-Machine (M2M) communication has led to a new paradigm of Internet of Things (IoT). The future of M2M communication in smart home lies in the aggregation and allocation of resources and service provisioning of diverse applications using different radio technologies. M2M communication may operate on the virtual sensor network to provide independent applications running on heterogeneous network simultaneously. M2M is going to play a major role in the area of Smart Home and Ambient Assisted Living (SHAAL) providing assistance to the elderly people with smart sensors that monitor the home environment and provides aid health monitoring to human requiring medical assistance. The current state of the art frameworks are dedicated to specific applications with the support of single radio network with limited service provisioning options. However, in order to fully exploit the resources in this paper we present a service provisioning framework realization of M2M in virtual sensor n...
2015 5th National Symposium on Information Technology: Towards New Smart World (NSITNSW), 2015
Wireless Sensor Network (WSN) has led to a new paradigm of Internet of Everything (IoE). In case ... more Wireless Sensor Network (WSN) has led to a new paradigm of Internet of Everything (IoE). In case of Ambient Assisted Living (AAL) that is based on the sensor network is usually deployed for single application. However, the future of WSNs based on sensors lies in the multiple application support and the aggregation of resources either in the form of hardware or software. To deal with the challenges of aggregation of sensors in the health care environment, virtualization of a sensor network is an evolving concept that enables aggregation of multiple independent heterogeneous sensor networks under one roof. In order to virtualize the sensors and networks, middleware layer role is the most dominant one. Furthermore, middleware for sensors poses the overhead challenges like processing time, memory utilization, sampling rate, delay, and power consumption. In this paper efforts have been put forward by proposing a middleware framework for sensor network that uses multi-threading technique that increases the sampling frequency and reduces the delay caused by the hardware abstraction layer that resides on top each sensor node. Mathematical model shows significant improvement in the processing time.
Wireless Sensor Network (WSN) is leading to a new paradigm of Internet of Everything (IoE). WSNs ... more Wireless Sensor Network (WSN) is leading to a new paradigm of Internet of Everything (IoE). WSNs have a wide range of applications but are usually deployed in a particular application. However, the future of WSNs lies in the aggregation and allocation of resources, serving diverse applications. WSN virtualization by the middleware is an emerging concept that enables aggregation of multiple independent heterogeneous devices, networks, radios and software platforms; and enhancing application development. WSN virtualization, middleware can further be categorized into sensor virtualization and network virtualization. Middleware for WSN virtualization poses several challenges like efficient decoupling of networks, devices and software. In this paper efforts have been put forward to bring an overview of the previous and current middleware designs for WSN virtualization, the design goals, software architectures, abstracted services, testbeds and programming techniques. Furthermore, the paper also presents the proposed model, challenges and future opportunities for further research in the middleware designs for WSN virtualization.
2013 IEEE International Conference on Signal and Image Processing Applications, 2013
Interference Management (1M) is one of the major challenges of next generation wireless communica... more Interference Management (1M) is one of the major challenges of next generation wireless communication. Fractional Frequency Reuse (FFR) has been acknowledged as an efficient 1M technique, which offers significant capacity enhancement and improve cell edge coverage with low complexity. In literature, FFR has been analyzed mostly with cellular networks described by Hexagon Grid Model, which is neither tractable nor scalable to the dense deployment of next generation wireless networks. Moreover, the perfect geometry based grid model tends to overestimate the system performance and not able to reflect the reality. In this paper, we use the stochastic geometry approach, FFR is analyzed with cellular network modeled by homogeneous Poisson Point Process (PPP). A dynamic frequency allocation scheme is proposed which take into account the randomness of the cell coverage area describe by Voronoi tessellation. It is shown that the proposed scheme outperforms the traditional fixed frequency allocation schemes in terms of per user capacity and capacity density.
2013 IEEE Symposium on Wireless Technology & Applications (ISWTA), 2013
Machine-to-Machine (M2M) communication in cellular network is the driver for the future Internet ... more Machine-to-Machine (M2M) communication in cellular network is the driver for the future Internet of Things (IoT). The main challenge of M2M communication is the possibility of huge traffic in the uplink network that can cause problem in the network. This paper considers the problem of resource allocation among machines connecting in uplink to different femto base stations (FBSs). Resource allocation problem is analyzed through both non-cooperative and cooperative game to maximize their data rate and minimize utilization of power. Numerical result shows that by adapting non-cooperative game, all machines are getting data rate as per Nash Equilibrium (NE) or either they can set their strategy to maximize their data rate selfishly. On the other hand for coalitional game theory approach machines who participate in game are getting fair resource allocations.
Abstract: Wireless Sensor Network (WSN) is leading to a new paradigm of Internet of
Everything (I... more Abstract: Wireless Sensor Network (WSN) is leading to a new paradigm of Internet of Everything (IoE). WSNs have a wide range of applications but are usually deployed in a particular application. However, the future of WSNs lies in the aggregation and allocation of resources, serving diverse applications. WSN virtualization by the middleware is an emerging concept that enables aggregation of multiple independent heterogeneous devices, networks, radios and software platforms; and enhancing application development. WSN virtualization, middleware can further be categorized into sensor virtualization and network virtualization. Middleware for WSN virtualization poses several challenges like efficient decoupling of networks, devices and software. In this paper efforts have been put forward to bring an overview of the previous and current middleware designs for WSN virtualization, the design goals, software architectures, abstracted services, testbeds and programming techniques. Furthermore, the paper also presents the proposed model, challenges and future opportunities for further research in the middleware designs for WSN virtualization.
Machine-to-Machine (M2M) communication has led to a new paradigm of Internet of Things (IoT). The... more Machine-to-Machine (M2M) communication has led to a new paradigm of Internet of Things (IoT). The future of M2M communication in smart home lies in the aggregation and allocation of resources and service provisioning of diverse applications using different radio technologies. M2M communication may operate on the virtual sensor network to provide independent applications running on heterogeneous network simultaneously. M2M is going to play a major role in the area of Smart Home and Ambient Assisted Living (SHAAL) providing assistance to the elderly people with smart sensors that monitor the home environment and provides aid health monitoring to human requiring medical assistance. The current state of the art frameworks are dedicated to specific applications with the support of single radio network with limited service provisioning options. However, in order to fully exploit the resources in this paper we present a service provisioning framework realization of M2M in virtual sensor network for SHAAL, which allows independent parties to work together in a secure and reliable manner. In addition to this, the framework is designed to include benefits of Service Oriented Architecture (SOA) and Resource Oriented Architecture (ROA) along with the use of different low power, low data rate protocols. A middleware is used as a platform to link the underlying virtual networks with various applications. The network virtualization approach is adopted to design an efficient middleware framework that can effectively discover and manage the underlying network resources and provide services at home gateway. The framework will be used as the basis for the development of the SHAAL networked system.
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Papers by Zubair Khalid
Everything (IoE). WSNs have a wide range of applications but are usually deployed in a
particular application. However, the future of WSNs lies in the aggregation and allocation
of resources, serving diverse applications. WSN virtualization by the middleware is an
emerging concept that enables aggregation of multiple independent heterogeneous devices,
networks, radios and software platforms; and enhancing application development. WSN
virtualization, middleware can further be categorized into sensor virtualization and network
virtualization. Middleware for WSN virtualization poses several challenges like efficient
decoupling of networks, devices and software. In this paper efforts have been put forward to
bring an overview of the previous and current middleware designs for WSN virtualization,
the design goals, software architectures, abstracted services, testbeds and programming
techniques. Furthermore, the paper also presents the proposed model, challenges and future
opportunities for further research in the middleware designs for WSN virtualization.
Everything (IoE). WSNs have a wide range of applications but are usually deployed in a
particular application. However, the future of WSNs lies in the aggregation and allocation
of resources, serving diverse applications. WSN virtualization by the middleware is an
emerging concept that enables aggregation of multiple independent heterogeneous devices,
networks, radios and software platforms; and enhancing application development. WSN
virtualization, middleware can further be categorized into sensor virtualization and network
virtualization. Middleware for WSN virtualization poses several challenges like efficient
decoupling of networks, devices and software. In this paper efforts have been put forward to
bring an overview of the previous and current middleware designs for WSN virtualization,
the design goals, software architectures, abstracted services, testbeds and programming
techniques. Furthermore, the paper also presents the proposed model, challenges and future
opportunities for further research in the middleware designs for WSN virtualization.