Abstract: Fiber-Wireless (FiWi) networks are a promising candidate for future broadband access networks. These networks combine the optical network as the back end where different passive optical network (PON) technologies are realized and the wireless network as the front end where different wireless technologies are adopted, e.g. LTE, WiMAX, Wi-Fi, and Wireless Mesh Networks (WMNs). The convergence of both optical and wireless technologies requires designing architectures with robust efficient and effective bandwidth allocation schemes. Different bandwidth allocation algorithms have been proposed in FiWi networks aiming to enhance the different segments of FiWi networks including wireless and optical subnetworks. In this survey, we focus on the differentiating between the different bandwidth allocation algorithms according to their enhancement segment of FiWi networks. We classify these techniques into wireless, optical and Hybrid bandwidth allocation techniques.
Abstract: Radio Frequency Identification (RFID) has become a
key technology in the emerging concept of Internet of Things (IoT).
Naturally, business applications would require the deployment of
various RFID systems developed by different vendors that use
different data formats and structures. This heterogeneity poses a
challenge in developing real-life IoT systems with RFID, as
integration is becoming very complex and challenging. Semantic
integration is a key approach to deal with this challenge. To do so,
ontology for RFID systems need to be developed in order to
annotated semantically RFID systems, and hence, facilitate their
integration. Accordingly, in this paper, we propose ontology for
RFID systems. The proposed ontology can be used to semantically
enrich RFID systems, and hence, improve their usage and reasoning.
Abstract: Many wireless sensor network applications require
K-coverage of the monitored area. In this paper, we propose a
scalable harmony search based algorithm in terms of execution
time, K-Coverage Enhancement Algorithm (KCEA), it attempts to
enhance initial coverage, and achieve the required K-coverage degree
for a specific application efficiently. Simulation results show that
the proposed algorithm achieves coverage improvement of 5.34%
compared to K-Coverage Rate Deployment (K-CRD), which achieves
1.31% when deploying one additional sensor. Moreover, the proposed
algorithm is more time efficient.