Limits on Fundamental Limits to Computation

An indispensable part of our lives, computing has also become essential to industries and governments. Steady improvements in computer hardware have been supported by periodic doubling of transistor densities in integrated circuits over the last fifty years. Such Moore scaling now requires increasingly heroic efforts, stimulating research in alternative hardware and stirring controversy. To help evaluate emerging technologies and enrich our understanding of integrated-circuit scaling, we review fundamental limits to computation: in manufacturing, energy, physical space, design and verification effort, and algorithms. To outline what is achievable in principle and in practice, we recall how some limits were circumvented, compare loose and tight limits. We also point out that engineering difficulties encountered by emerging technologies may indicate yet-unknown limits.Comment: 15 pages, 4 figures, 1 tabl

Wireless Sensor Data Transport, Aggregation and Security

abstract: Wireless sensor networks (WSN) and the communication and the security therein have been gaining further prominence in the tech-industry recently, with the emergence of the so called Internet of Things (IoT). The steps from acquiring data and making a reactive decision base on the acquired sensor measurements are complex and requires careful execution of several steps. In many of these steps there are still technological gaps to fill that are due to the fact that several primitives that are desirable in a sensor network environment are bolt on the networks as application layer functionalities, rather than built in them. For several important functionalities that are at the core of IoT architectures we have developed a solution that is analyzed and discussed in the following chapters. The chain of steps from the acquisition of sensor samples until these samples reach a control center or the cloud where the data analytics are performed, starts with the acquisition of the sensor measurements at the correct time and, importantly, synchronously among all sensors deployed. This synchronization has to be network wide, including both the wired core network as well as the wireless edge devices. This thesis studies a decentralized and lightweight solution to synchronize and schedule IoT devices over wireless and wired networks adaptively, with very simple local signaling. Furthermore, measurement results have to be transported and aggregated over the same interface, requiring clever coordination among all nodes, as network resources are shared, keeping scalability and fail-safe operation in mind. Furthermore ensuring the integrity of measurements is a complicated task. On the one hand Cryptography can shield the network from outside attackers and therefore is the first step to take, but due to the volume of sensors must rely on an automated key distribution mechanism. On the other hand cryptography does not protect against exposed keys or inside attackers. One however can exploit statistical properties to detect and identify nodes that send false information and exclude these attacker nodes from the network to avoid data manipulation. Furthermore, if data is supplied by a third party, one can apply automated trust metric for each individual data source to define which data to accept and consider for mentioned statistical tests in the first place. Monitoring the cyber and physical activities of an IoT infrastructure in concert is another topic that is investigated in this thesis.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

From Sensing to Predictions and Database Technique: A Review of TV White Space Information Acquisition in Cognitive Radio Networks

Strategies to acquire white space information is the single most significant functionality in cognitive radio networks (CRNs) and as such, it has gone some evolution to enhance information accuracy. The evolution trends are spectrum sensing, prediction algorithm and recently, geo-location database technique. Previously, spectrum sensing was the main technique for detecting the presence/absence of a primary user (PU) signal in a given radio frequency (RF) spectrum. However, this expectation could not materialized as a result of numerous technical challenges ranging from hardware imperfections to RF signal impairments. To convey the evolutionary trends in the development of white space information, we present a survey of the contemporary advancements in PU detection with emphasis on the practical deployment of CRNs i.e. Television white space (TVWS) networks. It is found that geo-location database is the most reliable technique to acquire TVWS information although, it is financially driven. Finally, using financially driven database model, this study compared the data-rate and spectral efficiency of FCC and Ofcom TV channelization. It was discovered that Ofcom TV channelization outperforms FCC TV channelization as a result of having higher spectrum bandwidth. We proposed the adoption of an all-inclusive TVWS information acquisition model as the future research direction for TVWS information acquisition techniques

When the Hammer Meets the Nail: Multi-Server PIR for Database-Driven CRN with Location Privacy Assurance

We show that it is possible to achieve information theoretic location privacy for secondary users (SUs) in database-driven cognitive radio networks (CRNs) with an end-to-end delay less than a second, which is significantly better than that of the existing alternatives offering only a computational privacy. This is achieved based on a keen observation that, by the requirement of Federal Communications Commission (FCC), all certified spectrum databases synchronize their records. Hence, the same copy of spectrum database is available through multiple (distinct) providers. We harness the synergy between multi-server private information retrieval (PIR) and database- driven CRN architecture to offer an optimal level of privacy with high efficiency by exploiting this observation. We demonstrated, analytically and experimentally with deployments on actual cloud systems that, our adaptations of multi-server PIR outperform that of the (currently) fastest single-server PIR by a magnitude of times with information theoretic security, collusion resiliency, and fault-tolerance features. Our analysis indicates that multi-server PIR is an ideal cryptographic tool to provide location privacy in database-driven CRNs, in which the requirement of replicated databases is a natural part of the system architecture, and therefore SUs can enjoy all advantages of multi-server PIR without any additional architectural and deployment costs.Comment: 10 pages, double colum

A DIVERSE BAND-AWARE DYNAMIC SPECTRUM ACCESS ARCHITECTURE FOR CONNECTIVITY IN RURAL COMMUNITIES

Ubiquitous connectivity plays an important role in improving the quality of life in terms of economic development, health and well being, social justice and equity, as well as in providing new educational opportunities. However, rural communities which account for 46% of the world\u27s population lacks access to proper connectivity to avail such societal benefits, creating a huge digital divide between the urban and rural areas. A primary reason is that the Information and Communication Technologies (ICT) providers have less incentives to invest in rural areas due to lack of promising revenue returns. Existing research and industrial attempts in providing connectivity to rural communities suffer from severe drawbacks, such as expensive wireless spectrum licenses and infrastructures, under- and over-provisioning of spectrum resources while handling heterogeneous traffic, lack of novel wireless technologies tailored to the unique challenges and requirements of rural communities (e.g., agricultural fields). Leveraging the recent advances in Dynamic Spectrum Access (DSA) technologies like wide band spectrum analyzers and spectrum access systems, and multi-radio access technologies (multi-RAT), this dissertation proposes a novel Diverse Band-aware DSA (d-DSA) network architecture, that addresses the drawbacks of existing standard and DSA wireless solutions, and extends ubiquitous connectivity to rural communities; a step forward in the direction of the societal and economic improvements in rural communities, and hence, narrowing the digital divide between the rural and urban societies. According to this paradigm, a certain wireless device is equipped with software defined radios (SDRs) that are capable of accessing multiple (un)licensed spectrum bands, such as, TV, LTE, GSM, CBRS, ISM, and possibly futuristic mmWaves. In order to fully exploit the potential of the d-DSA paradigm, while meeting heterogeneous traffic demands that may be generated in rural communities, we design efficient routing strategies and optimization techniques, which are based on a variety of tools such as graph modeling, integer linear programming, dynamic programming, and heuristic design. Our results on realistic traces in a large variety of rural scenarios show that the proposed techniques are able to meet the heterogeneous traffic requirements of rural applications, while ensuring energy efficiency and robustness of the architecture for providing connectivity to rural communities

Optimal Real-time Spectrum Sharing between Cooperative Relay and Ad-hoc Networks

Optimization based spectrum sharing strategies have been widely studied. However, these strategies usually require a great amount of real-time computation and significant signaling delay, and thus are hard to be fulfilled in practical scenarios. This paper investigates optimal real-time spectrum sharing between a cooperative relay network (CRN) and a nearby ad-hoc network. Specifically, we optimize the spectrum access and resource allocation strategies of the CRN so that the average traffic collision time between the two networks can be minimized while maintaining a required throughput for the CRN. The development is first for a frame-level setting, and then is extended to an ergodic setting. For the latter setting, we propose an appealing optimal real-time spectrum sharing strategy via Lagrangian dual optimization. The proposed method only involves a small amount of real-time computation and negligible control delay, and thus is suitable for practical implementations. Simulation results are presented to demonstrate the efficiency of the proposed strategies.Comment: One typo in the caption of Figure 5 is correcte

A comparative investigation on performance and which is the preferred methodology for spectrum management; geo-location spectrum database or spetrum sensing

A Research Report submitted to the Faculty of Engineering and the Built Environment, University of Witwatersrand, in the partial fulfilment of the requirements for the degree of Master of Science in Engineering Johannesburg, 2015.Due to the enormous demand for multimedia services which relies hugely on the availability of spectrum, service providers and technologist are devising a means or method which is able to fully satisfy these growing demands. The availability of spectrum to meet these demands has been a lingering issue for the past couple of years. Many would have it tagged as spectrum scarcity but really the main problem is not how scarce the spectrum is but how efficiently allocated to use is the spectrum. Once such inefficiency is tackled effectively, then we are a step closer in meeting the enormous demands for uninterrupted services. However, to do so, there are techniques or methodologies being developed to aid in the efficient management of spectrum. In this research project, two methodologies were considered and the efficiency of these methodologies in the areas of spectrum management. The Geo-location Spectrum Database (GLSD) which is the most adopted technique and the Cognitive radio spectrum sensing technique are currently the available techniques in place. The TV whitespaces (TVWS) was explored using both techniques and certain comparison based on performances; implementation, practicability, cost and flexibility were used as an evaluation parameter in arriving at a conclusion. After accessing both methodologies, conclusions were deduced on the preferred methodology and how its use would efficiently solve the issues encountered in spectrum managemen

Parsing for agile modeling

Agile modeling refers to a set of methods that allow for a quick initial development of an importer and its further refinement. These requirements are not met simultaneously by the current parsing technology. Problems with parsing became a bottleneck in our research of agile modeling. In this thesis we introduce a novel approach to specify and build parsers. Our approach allows for expressive, tolerant and composable parsers without sacrificing performance. The approach is based on a context-sensitive extension of parsing expression grammars that allows a grammar engineer to specify complex language restrictions. To insure high parsing performance we automatically analyze a grammar definition and choose different parsing strategies for different parts of the grammar. We show that context-sensitive parsing expression grammars allow for highly composable, tolerant and variable-grained parsers that can be easily refined. Different parsing strategies significantly insure high-performance of parsers without sacrificing expressiveness of the underlying grammars