Development of new data partitioning and allocation algorithms for query optimization of distributed data warehouse systems

Distributed databases and in particular distributed data warehousing are becoming an increasingly important technology for information integration and data analysis. Data Warehouse (DW) systems are used by decision makers for performance measurement and decision support. However, although data warehousing and on-line analytical processing (OLAP) are essential elements of decision support, the OLAP query response time is strongly affected by the volume of data need to be accessed from storage disks. Data partitioning is one of the physical design techniques that may be used to optimize query processing cost in DWs. It is a non redundant optimization technique because it does not replicate data, contrary to redundant techniques like materialized views and indexes. The warehouse partitioning problem is concerned with determining the set of dimension tables to be partitioned and using them to generate the fact table fragments. In this work an enhanced grouping algorithm that avoids the limitations of some existing vertical partitioning algorithms is proposed. Furthermore, a static partitioning algorithm that allows fragmentation at early stages of schema design is presented. The thesis also, investigates the performance of the data warehouse after implementing a combination of Genetic Algorithm (GA) and Simulated Annealing (SA) techniques to horizontally partition the data warehouse star schema. It, then presents the experimentation and implementation results of the proposed algorithm. This research presented different approaches to optimize data fragments allocation cost using a greedy mathematical model and a combination of simulated annealing and genetic algorithm to determine the site by site allocation leading to optimal solutions for fragments distribution. Throughout this thesis, the term fragmentation and partitioning will be used interchangeably

Throughput evaluation for the downlink scenario of co-tier interference in heterogeneous network

To extend the coverage and capacity of Heterogeneous Networks (HetNets), femtocells (HeNodeBs) has been impressive to deploy in in-house or apartment. Owing to co-channel spectrum involvement these HeNodeB sources Co-Tier interference (CTI) with neighbor HeNodeBs and users of HeNodeB (HUE) in orthogonal frequency division multiplexing Access (OFDMA). As a result, CTI is occurred which causes of system throughput degradation. This paperinvestigates the OFDMA subcarrier allocation techniques and algorithms. A Genetic Algorithm based SubcarrierAllocation (GA-SA) framework is evaluated to enhanced throughput of HeNodeB and HUE. The enhancement of the system throughput and Signal to Interference Noise Ratio (SINR) is analyzed to mitigate CTI. The system level simulation is considered to evaluate the performance of the framework. The results show that the throughput is enhanced for HUE and HeNodeB, which can mitigate the CTI in OFDMA

Outage probability analysis of Co-Tier interference in heterogeneous network

In Heterogeneous Network (HetNet), the femtocell (HeNB) has been deployed by the telecommunication industries to provide extensive coverage as well as capacity in an indoor. These HeNBs are Customer Premise Equipment (CPE) which is randomly used in co-channel with macrocell (MeNB) and causes the Co-Tier Interference (CTI) in OFDMA. The effect of CTI in OFDMA systems can lead the system throughput degradation and service disruption. Because of quick direct changing features in Rayleigh channel, it is compulsory to succeed the satisfactory performance. The signal-to-interference noise ratio (SINR) is arbitrary which drives the highest capacity to be an irregular variable. However, this paper derives the expressions of outage probabilities based on the hybrid Genetic Algorithm (GA) with biogeography based dynamic subcarrier allocation (HGBBDSA) algorithm is implemented in reducing the outage probability. The outage probability countenance is expressed for the moment-generating function of the total SINR at the receivers end. The simulation results demonstrate that the HGBBDSA can lessen the outage to 45 % than existing methods

BALANITES KERNEL OIL FOR THE TREATMENT OF DERMATOPHYTES: A CLINICAL TRIAL

In a previous in vitro study, we have shown that the kernel oil of fruits of the tree Balanites aegyptiaca referred to as Balanites kernel oil ((BKO) is active against dermatophytes (i.e. superficial mycosis, ringworms, tineas (T. captitis, T. cercinata and T. pedis). We report here our clinical trials with BKO. Trials were performed on patients presenting at Wad Medani Dermatology Teaching Hospital as well as primary school children in Elsoreeba Town (5 km south of Wad Medani). Not all patients followed treatment till completely cured. Patients treated with BKO (half of the total) achieved complete cure in 3-5 weeks, on average, while those treated with the standard antifungal drug Miconazole (half of the total patients) did the same in the longer period of 3-8 weeks. Photographs showing progress of response to BKO treatments are included. BKO has great potential for development as a commercial drug for the treatment of dermatophytes

A multihoming-based mobility management scheme to reduce registration delay on proxy MIPv6 domain in NEMO

Registration delay is a significant issue for mobile network due to increase traffic load with handoff latency at the time of frequent movement from one subnet to another of Mobile Router (MR) in NEMO Basic Support protocol (NEMO BSP). Hence, a network-based localized protocol (i.e. PMIPv6) is integrated with NEMO in order to solve these matters. Yet, combining this network-based localized protocol for inter mobility handoff (i.e. movement among different access technology) in NEMO environment is a challenging issue as both MR and its MNNs must be taken into consideration. Therefore, this paper proposes a multihoming-based Early Proxy Binding Update scheme in NEMO (EPBU-NEMO) which is based on FPMIPv6 with predictive mode to reduce registration delay during inter mobility handoff. Moreover, numerical framework is formulated to evaluate the outcomes of the EPBU-NEMO scheme. Lastly, it determines that EPBU-NEMO scheme outperforms the standard NEMO BSP related to signaling cost regardless of increasing the number of MRs as well as cell residence time

Connectivity, interoperability and manageability challenges in internet of things

he vision of Internet of Things (IoT) is about interconnectivity between sensors, actuators, people and processes. IoT exploits connectivity between physical objects like fridges, cars, utilities, buildings and cities for enhancing the lives of people through automation and data analytics. However, this sudden increase in connected heterogeneous IoT devices takes a huge toll on the existing Internet infrastructure and introduces new challenges for researchers to embark upon. This paper highlights the effects of heterogeneity challenges on connectivity, interoperability, management in greater details. It also surveys some of the existing solutions adopted in the core network to solve the challenges of massive IoT deployment. The paper finally concludes that IoT architecture and network infrastructure needs to be reengineered ground-up, so that IoT solutions can be safely and efficiently deployed

Performance analysis of constrained device virtualization algorithm

Internet of Things aims to automate and add intelligence into existing processes by introducing constrained devices such as sensors and actuators. These constrained devices lack in computation and memory resources and are usually battery powered for ease of deployments. Due to their limited capabilities, the constrained devices usually host proprietary protocols, platforms, data formats and data structures for communications and therefore, are unable to communicate with devices from different vendors. This inability leads to interoperability issues in Internet of Things which, is in fact against the spirit of Internet of things which, envisions interconnection of billions of devices and hence, results in an isolated, vendor-locked and close-loop deployments of IoT solutions. Various approaches have been made by the industry and academia to resolve the interoperability issues amongst constrained devices. However, majority of the solutions are at different layers of the communication stack but do not provide a holistic solution for the problem. In more recent research, there have been theoretical proposals to virtualize constrained devices to abstract their data so that its always available to applications. We have adopted this technique in our research to virtualize the entire Internet of Things network so that virtual TCP/IP based protocols can operate on virtual networks for enabling interoperability. This paper proposes the operations of the Constrained Device Virtualization Algorithm and then simulates it in CloudSIM to derive performance results. The paper further highlights open issues for future research in this area

Optimized RC timing technique for accurate measurement of minute capacitance changes

This paper presents a technique for accurate measurement of small capacitive changes. This is based on selecting the most linear part of the curve obtained by charging the capacitor undergoing changes through a known resistor value. This measurement is part of the design of a system for measuring blood glucose content non-invasively. The technique is based on measuring ultra-low low glucose levels in the blood as capacitive changes converted into RC timing constant optimized using a circuit set to trigger at an appropriate time activating a counter. The measured data is captured instant later, selecting the most linear part of the charging curve. The results so obtained are compared with the ones obtained through RC-timing standard procedure. The technique reported is with a remarkable low error of about 2.25% as against 11.78% by the standard RC-timing technique

May Measurement Month 2017: an analysis of blood pressure screening in Sudan-Northern Africa and Middle East

Elevated blood pressure (BP) is a growing burden worldwide, leading to over 10 million deaths each year. Sudan has the second highest prevalence of hypertension in North Africa. One in four people with a non-communicable disease has hypertension. May Measurement Month (MMM) is a global initiative, aimed at raising awareness of high BP to act as a temporary solution to the lack of screening programs worldwide. The MMM screening survey provided an opportunity to correlate between unique risk factors and BP levels among Sudanese population. Such an approach allows for directing efforts towards setting the appropriate preventive measures as opposed to disease treatment. An opportunistic cross-sectional survey of volunteers aged ≥18 was carried out in May 2017. Blood pressure measurement, the definition of hypertension and statistical analysis followed the standard MMM protocol. The study was conducted at 100 sites distributed in four states: Khartoum, Gezira, Blue Nile, and Kassala. Overall, a total of 44 413 participants were enrolled in the survey. After imputation, 7332 out of 44 118 participants with an available mean of the second and third readings had hypertension (16.6%). A total of 6956 (15.9%) participants were found to have hypertension of the 43 742 who were not receiving treatment. Among participants who were on treatment, 155 out of 374 (41.3%) had uncontrolled BP. After adjusting for age and sex, systolic and diastolic BP's were significantly higher in those receiving antihypertensive treatment, with a previous history of stroke and with elevated body mass index. Systolic BP was significantly higher in people with diabetes and with previous myocardial infarction. Smoking was associated with increased diastolic BP and decreased systolic BP. Alcohol intake as well as BP measurement on left vs. right arm had no association with BP reading. The MMM17 was the largest BP screening campaign ever held in the country. A considerable percentage of detected hypertensives were not on treatment with a significant proportion of uncontrolled hypertension among those on treatment. These results suggest that opportunistic screening can identify significant numbers with raised BP