Hassnaa Moustafa

Mobile wearable communications [Guest Editorial]

This special issue provides the latest research and development on wireless mobile wearable communications. According to a report by Juniper Research, the market value of connected wearable devices is expected to reach

An Architectural Vision for a Data-Centric IoT: Rethinking Things, Trust and Clouds

1.5 billion by 2014, and the shipment of wearable devices may reach 70 million by 2017. Good examples of wearable devices are the prominent Google Glass and Microsoft HoloLens. As wearable technology is rapidly penetrating our daily life, mobile wearable communication is becoming a new communication paradigm. Mobile wearable device communications create new challenges compared to ordinary sensor networks and short-range communication. In mobile wearable communications, devices communicate with each other in a peer-to-peer fashion or client-server fashion and also communicate with aggregation points (e.g., smartphones, tablets, and gateway nodes). Wearable devices are expected to integrate multiple radio technologies for various applications’ needs with small power consumption and low transmission delays. These devices can hence collect, interpret, transmit, and exchange data among supporting components, other wearable devices, and the Internet. Such data are not limited to peoples personal biomedical information but also include human-centric social and contextual data. The success of mobile wearable technology depends on communication and networking architectures that support efficient and secure end-to-end information flows. A key design consideration of future wearable devices is the ability to ubiquitously connect to smartphones or the Internet with very low energy consumption. Radio propagation and, accordingly, channel models are also different from those in other existing wireless technologies. A huge number of connected wearable devices require novel big data processing algorithms, efficient storage solutions, cloud-assisted infrastructures, and spectrum-efficient communications technologies.

Context-adaptive cross-layer TCP optimization for Internet video streaming

The Internet of Things (IoT) is producing a tidal wave of data, much of it originating at the network edge, from applications with requirements unmet by the traditional back-end Cloud architecture. To address the disruption caused by the overabundance of data, this paper offers a holistic data-centric architectural vision for the data-centric IoT. It advocates that we rethink our approach to the design and definition of key elements: that we shift our focus from Things to Smart Objects; grow Trust organically; and evolve back-end Clouds toward Edge and Fog clouds, which leverage data-centric networks and enable optimal handling of upstream data flows. Along the way, we wax poetic about several blue-sky topics, assess the status of these elements in the context of related work, and identify known gaps in meeting this vision.

Optimal placement algorithm (OPA) for IoT over ICN

The tremendous growth of video content over the Internet and evolution towards more personalized video applications has led to a need for a network and service infrastructure better suited to todays content and mobility needs. Quality of Experience (QoE) management is one of the major challenges for video delivery given the limited bandwidth for wireless access network causing video packet drops and the core network congestion impacting video service delay. In this context, the current TCP-based model used for HTTP streaming presents challenges due to throughput variation and high latency. We present a context-adaptive cross-layer optimization approach to enhance video streaming over TCP that introduces network and content awareness in TCP operation to provide adaptive reliability and smoother throughput. Our proposed solution requires implementation changes only on the receiver side without impacting the TCP sender implementation. We validated the proposed solution through OPNET simulations and the results show some significant performance gains in both TCP throughput and video QoE metrics.

Media content streaming

Information Centric Networks (ICN) is very promising for Internet of Things (IoT) deployment, where the data-centric approach is useful in reducing the data retrieval latency as well as the network traffic for IoT services. Also, the innetwork caching capabilities in ICN limits the massive data access to the data producers and so relaxes the need of continuous connectivity E2E connectivity between data producers and data consumers (this helps power efficiency as IoT devices can enter in sleep mode when they are not transmitting data). In this paper, we present an ICN-IoT architecture in which ICN nodes provide IoT gateways capabilities and ICN caching functions. Optimal Placement Algorithm (OPA) is proposed to choose the optimal placement location for ICN nodes. We evaluated OPA with respect to several performance metrics and the obtained results show improvement in services consumption latency and network load. Furthermore, we propose a caching strategy that shows to stabilize the network load despite any increase in the number of consumer interests.