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The era of Big Data is here now, which has brought both unprecedented opportunities and critical challenges. In this article, from a perspective of cognitive wireless networking, we start with a definition of Big Spectrum Data by analyzing its characteristics in terms of six Vs, i.e., volume, variety, velocity, veracity, viability, and value. We then present a high-level tutorial on research frontiers in Big Spectrum Data analytics to guide the development of practical algorithms. We also highlight Big Spectrum Data as the new resource for cognitive wireless networking by presenting the emerging use cases.

Information centric networking (ICN) proposes to redesign the Internet by replacing its host-centric design with information-centric design. Communication among entities is established at the naming level, with the receiver side (referred to as the Consumer) acting as the driving force behind content delivery, by interacting with the network through Interest message transmissions. One of the proposed advantages for ICN is its support for mobility, by de-coupling applications from transport semantics. However, so far, little research has been conducted to understand the interaction between ICN and mobility of consuming and producing applications, in protocols purely based on information-centric principles, particularly in the case of NDN. In this paper, we present our findings on the mobility-based performance of Named Data Networking (NDN) in wireless access networks. Through simulations, we show that the current NDN architecture is not efficient in handling mobility and architectural enhancements needs to be done to fully support mobility of Consumers and Producers.

The IEEE 802.11a high-speed wireless local area networking (WLAN) protocol does not specify a mechanism for dynamically altering network data rates based on changing link conditions. This thesis first presents a baseline software model of the 802.11a protocol developed using the OPNET simulation tool. The model includes both the medium access control (MAC) and physical (PHY) layers of the standard. Two data rate agility mechanisms are then proposed and analyzed using the model. An infrastructure WLAN implementation of the baseline model is first simulated under standard network conditions to verify its operational characteristics and the results are presented. The model is then used to simulate two data rate agility mechanisms, one based on the link signal-to-noise ratio (SNR) and the other based on the frame loss rate at the transmitting Station. Each technique is simulated using an infrastructure WLAN consisting of a fixed access point and a mobile workstation operating with standard network traffic loads. The results indicate that the link SNR is a better decision criterion for data rate agility than the frame loss rate. The design and methodology of this analysis provides insight into dynamic rate agility mechanisms and the criteria that may be used in developing in future 802.11 a-compliant hardware imlementations.

The IEEE 802.11a high-speed wireless local area networking (WLAN) protocol does not specify a mechanism for dynamically altering network data rates based on changing link conditions. This thesis first presents a baseline software model of the 802.11a protocol developed using the OPNET simulation tool. The model includes both the medium access control (MAC) and physical (PHY) layers of the standard. Two data rate agility mechanisms are then proposed and analyzed using the model. An infrastructure WLAN implementation of the baseline model is first simulated under standard network conditions to verify its operational characteristics and the results are presented. The model is then used to simulate two data rate agility mechanisms, one based on the link signal- to-noise ratio (SNR) and the other based on the frame loss rate at the transmitting Station. Each technique is simulated using an infrastructure WLAN consisting of a fixed access point and a mobile workstation operating with standard network traffic loads. The results indicate that the link SNR is a better decision criterion for data rate agility than the frame loss rate. The design and methodology of this analysis provides insight into dynamic rate agility mechanisms and the criteria that may be used in developing in future 802.11 a-compliant hardware imlementations.

The IEEE 802.11a high-speed wireless local area networking (WLAN) protocol does not specify a mechanism for dynamically altering network data rates based on changing link conditions. This thesis first presents a baseline software model of the 802.11a protocol developed using the OPNET simulation tool. The model includes both the medium access control (MAC) and physical (PHY) layers of the standard. Two data rate agility mechanisms are then proposed and analyzed using the model. An infrastructure WLAN implementation of the baseline model is first simulated under standard network conditions to verify its operational characteristics and the results are presented. The model is then used to simulate two data rate agility mechanisms, one based on the link signal- to-noise ratio (SNR) and the other based on the frame loss rate at the transmitting Station. Each technique is simulated using an infrastructure WLAN consisting of a fixed access point and a mobile workstation operating with standard network traffic loads. The results indicate that the link SNR is a better decision criterion for data rate agility than the frame loss rate. The design and methodology of this analysis provides insight into dynamic rate agility mechanisms and the criteria that may be used in developing in future 802.11 a-compliant hardware imlementations.

The IEEE 802.11a high-speed wireless local area networking (WLAN) protocol does not specify a mechanism for dynamically altering network data rates based on changing link conditions. This thesis first presents a baseline software model of the 802.11a protocol developed using the OPNET simulation tool. The model includes both the medium access control (MAC) and physical (PHY) layers of the standard. Two data rate agility mechanisms are then proposed and analyzed using the model. An infrastructure WLAN implementation of the baseline model is first simulated under standard network conditions to verify its operational characteristics and the results are presented. The model is then used to simulate two data rate agility mechanisms, one based on the link signal- to-noise ratio (SNR) and the other based on the frame loss rate at the transmitting Station. Each technique is simulated using an infrastructure WLAN consisting of a fixed access point and a mobile workstation operating with standard network traffic loads. The results indicate that the link SNR is a better decision criterion for data rate agility than the frame loss rate. The design and methodology of this analysis provides insight into dynamic rate agility mechanisms and the criteria that may be used in developing in future 802.11 a-compliant hardware imlementations.