Urban Planning Using a Geospatial Approach: A Case Study of Libya

Large scale developmental projects firstly require the selection of one or more cities to be developed. In Libya, the selection process is done by selected organizations, which is highly influenced by human judgement that can be inconsiderate of socioeconomic and environmental factors. In this study, we propose an automated selection process, which takes into consideration only the important factors for city (cities) selection. Specifically, a geospatial decision-making tool, free of human bias, is proposed based on the fuzzy overlay (FO) and technique for order performance by similarity to ideal solution (TOPSIS) techniques for development projects in Libya. In this work, a dataset of 17 evaluation criteria (GIS factors) across five urban conditioning factors were prepared. The dataset served as input to the FO model to calculate weights (importance) for each criterion. A support vector machine (SVM) classifier was then trained to refine weights from the FO model. TOPSIS was then applied on the refined results to rank the cities for development. Experimental results indicate promising overall accuracy and kappa statistics. Our findings also show that highest and lowest success rates are 0.94 and 0.79, respectively, while highest and lowest prediction rates are 0.884 and 0.673, respectively

Seamless Application Handover Across Radio Access Networks (SAHARA Net)

The explosion in mobile and data traffic in the last decade has led to a rapid proliferation in wireless networks. A plethora of wireless access technologies are available today each with a different offering. Some offer high data rates within a restricted coverage area such as 802.11 hotspots. Others, offer lower data rates but with a much wider coverage such as UMTS. This diversity can be harnessed in a way that creates a ubiquitous communications platform for the user. This is the premise of the heterogeneous networks vision/architecture: an environment where disparate technologies cooperate together and complement each other. However, there are various technical challenges in the way of such convergence. The first obstacle is enabling communication between disparate mobility protocols. Once this is achieved, the diversity of networks in itself poses a challenge for the user as to which network he connects to. This thesis answers the first question by reviewing the low-latency handover literature to identify the most credible solutions. The general consensus amongst researchers in the field has been to bridge the gap between the network and link layers so that IP protocols can react quickly to link changes. To answer the second question, this thesis defines a framework to assess handover decision algorithms based on application performance. The merit of the handover algorithm’s decision is measured by how well the application performs after handover. In order to facilitate this process, a simulation module was created within the NS2 network simulator that allows mobile devices to collect network measurements and feed that information into a decision algorithm to decide whether or not handover should be triggered. Through this evaluation process, a number of issues emerged as possible stumbling blocks. The first such issue is the inconsistency between local network conditions measured at the Access Point or Base Station, and the end to end conditions experienced by the user’s application. Another issue is the algorithm’s adaptability to user and application preferences. Personal users might be cost aware opting to trade off quality for a lower cost in certain circumstances. The Abstract IV handover algorithm must be able to accommodate such scenarios. Furthermore, algorithms must be able to adapt their decisions according to the application’s requirements. Using application profiles with thresholds or utility functions can result in better decisions than using absolute values. If an application is satisfied with the current network conditions, it might not be in its benefit to move to a different network even if it offered better conditions. In fact, it might suffer as a result of possible handover disruptions

Access Network Selection in a 4G Networking Environment

An all-IP pervasive networking system provides a comprehensive IP solution where voice, data and streamed multimedia can be delivered to users at anytime and anywhere. Network selection is a key issue in this converged heterogeneous networking environment. A traditional way to select a target network is only based on the received signal strength (RSS); however, it is not comprehensive enough to meet the various demands of different multimedia applications and different users. Though some existing schemes have considered multiple criteria (e.g. QoS, security, connection cost, etc.) for access network selection, there are still several problems unsettled or not being solved perfectly. In this thesis, we propose a novel model to handle this network selection issue. Firstly, we take advantage of IEEE 802.21 to obtain the information of neighboring networks and then classify the information into two categories: 1) compensatory information and 2) non-compensatory information; secondly, we use the non-compensatory information to sort out the capable networks as candidates. If a neighboring network satisfies all the requirements of non-compensatory criteria, the checking of the compensatory information will then be triggered; thirdly, taking the values of compensatory information as input, we propose a hybrid ANP and RTOPSIS model to rank the candidate networks. ANP elicit weights to compensatory criteria and eliminates the interdependence impact on them, and RTOPSIS resolves the rank reversal problem which happens in some multiple criteria decision making (MCDM) algorithms such as AHP, TOPSIS, and ELECTRE. The evaluation study verifies the usability and validity of our proposed network selection method. Furthermore, a comparison study with a TOPSIS based algorithm shows the advantage and superiority of the proposed RTOPSIS based model

Context-aware multi-attribute decision multi - attribute decision making for radio access technology selection in ultra dense network

Ultra Dense Network (UDN) is the extreme densification of heterogeneous Radio Access Technology (RAT) that is deployed closely in coordinated or uncoordinated manner. The densification of RAT forms an overlapping zone of signal coverage leading to the frequent service handovers among the RAT, thus degrading overall system performance. The current RAT selection approach is biased towards network-centric criteria pertaining to signal strength. However, the paradigm shift from network-centric to user-centric approach necessitates a multi-criteria selection process, with methodology relating to both network and user preferences in the context of future generation networks. Hence, an effective selection approach is required to avoid unnecessary handovers in RAT. The main aim of this study is to propose the Context-aware Multiattribute decision making for RAT (CMRAT) selection for investigating the need to choose a new RAT and further determine the best amongst the available methods. The CMRAT consists of two mechanisms, namely the Context-aware Analytical Hierarchy Process (CAHP) and Context-aware Technique for Order Preference by Similarity to an Ideal Solution (CTOPSIS). The CAHP mechanism measures the need to switch from the current RAT, while CTOPSIS aids in decision making to choose the best target RAT. A series of experimental studies were conducted to validate the effectiveness of CMRAT for achieving improved system performance. The investigation utilises shopping mall and urban dense network scenarios to evaluate the performance of RAT selection through simulation. The findings demonstrated that the CMRAT approach reduces delay and the number of handovers leading to an improvement of throughput and packet delivery ratio when compared to that of the commonly used A2A4-RSRQ approach. The CMRAT approach is effective in the RAT selection within UDN environment, thus supporting heterogeneous RAT deployment in future 5G networks. With context-aware selection, the user-centric feature is also emphasized

Methodological review of multicriteria optimization techniques: aplications in water resources

Multi-criteria decision analysis (MCDA) is an umbrella approach that has been applied to a wide range of natural resource management situations. This report has two purposes. First, it aims to provide an overview of advancedmulticriteriaapproaches, methods and tools. The review seeks to layout the nature of the models, their inherent strengths and limitations. Analysis of their applicability in supporting real-life decision-making processes is provided with relation to requirements imposed by organizationally decentralized and economically specific spatial and temporal frameworks. Models are categorized based on different classification schemes and are reviewed by describing their general characteristics, approaches, and fundamental properties. A necessity of careful structuring of decision problems is discussed regarding planning, staging and control aspects within broader agricultural context, and in water management in particular. A special emphasis is given to the importance of manipulating decision elements by means ofhierarchingand clustering. The review goes beyond traditionalMCDAtechniques; it describes new modelling approaches. The second purpose is to describe newMCDAparadigms aimed at addressing the inherent complexity of managing water ecosystems, particularly with respect to multiple criteria integrated with biophysical models,multistakeholders, and lack of information. Comments about, and critical analysis of, the limitations of traditional models are made to point out the need for, and propose a call to, a new way of thinking aboutMCDAas they are applied to water and natural resources management planning. These new perspectives do not undermine the value of traditional methods; rather they point to a shift in emphasis from methods for problem solving to methods for problem structuring. Literature review show successfully integrations of watershed management optimization models to efficiently screen a broad range of technical, economic, and policy management options within a watershed system framework and select the optimal combination of management strategies and associated water allocations for designing a sustainable watershed management plan at least cost. Papers show applications in watershed management model that integrates both natural and human elements of a watershed system including the management of ground and surface water sources, water treatment and distribution systems, human demands,wastewatertreatment and collection systems, water reuse facilities,nonpotablewater distribution infrastructure, aquifer storage and recharge facilities, storm water, and land use

Network Selection in Wireless Heterogeneous Networks: a Survey, Journal of Telecommunications and Information Technology, 2018, nr 4

Heterogeneous wireless networks is a term referring to networks combining different radio access technologies with the aim of establishing the best connection possible. In this case, users with multi-mode terminals can connect via different wireless technologies, such as 802.16, 802.11, UMTS, HSPA and LTE, all at the same time. The problem consists in the selection of the most suitable from all radio access technologies available. The decision process is called network selection, and depends on several parameters, such as quality of service, mobility, cost, energy, battery life, etc. Several methods and approaches have been proposed in this context, with their objective being to offer the best QoS to the users, and/or to maximize re-usability of the networks. This paper represents a survey of the network selection methods used. Multiple attribute-dependent decision-making methods are presented. Furthermore, the game theory concept is illustrated, the use of the fuzzy logic is presented, and the utility functions defining the network selection process are discussed

Study of Locating Fire Stations using Linear Assignment Method : Case Study Maku City

Today excess density of population in city and it is increasing growth in bulk is led to demand and attention to urban development Demand for urban development is one of the most important issues against human in future Therefore to solve this problem and obstacles safety system of city should be developed along this to cover whole city The most important problem about the services of fire stations is the inappropriate distribution of stations and restricted function area of present stations So qualities and quantities distribution of stations is investigated scientifically and professionally Using traditional methods planning fire stations for services mean wasting papers and time but today using GIS serves as a tool to create proper and effective databas

A Genetic Algorithm-based Framework for Soft Handoff Optimization in Wireless Networks

In this paper, a genetic algorithm (GA)-based approach is used to evaluate the probability of successful handoff in heterogeneous wireless networks (HWNs) so as to increase capacity and network performance. The traditional handoff schemes are prone to ping pong and corner effects and developing an optimized handoff scheme for seamless, faster, and less power consuming handoff decision is challenging. The GA scheme can effectively optimize soft handoff decision by selecting the best fit network for the mobile terminal (MT) considering quality of service (QoS) requirements, network parameters and user’s preference in terms of cost of different attachment points for the MT. The robustness and ability to determine global optima for any function using crossover and mutation operations makes GA a promising solution. The developed optimization framework was simulated in Matrix Laboratory (MATLAB) software using MATLAB’s optima tool and results show that an optimal MT attachment point is the one with the highest handoff success probability value which determines direction for successful handoff in HWN environment. The system maintained a 90%  with 4 channels and more while a 75% was obtained even at high traffic intensity

Network Selection Optimization in a Secured Mobile IP Data Overlay System

The purpose of this thesis to so solve a limitation in the switchover mechanism of a Mobile IP (MIP) client device where it fails to change the active Mobile IP leg in a scenario where the current used path is just marginally good. The MIP client is a Cisco 819 router that provides internet connectivity to end users via an internal radio interface to a public Mobile Network Operator (MNO) and an external modem connected via an Ethernet port. When Mobile IP fails to properly select the active leg, the end user’s experience detriments and is unable to continue normal operation, this is why a mechanism is needed to probe the available networks and to select the best one for the end user. This work studies different vertical handover mechanisms that could be used in this type of environments where not only, not all the participants of the handover selection are radio interfaces; as in this case one interface is an external device, but also where most of the physical information of an interface is not available to use as part of a handover algorithm. This thesis proposes three different mechanisms to choose the best available network at any given time to complement the Mobile IP operation. The first mechanism is based on Round-Trip-Time (RTT), the next mechanism uses immediate throughput as the metric for the network selection and the final proposal is a muti-attribute algorithm where very poor networks will be filtered by their larger RTT values first and only then will the immediate available throughput will be measured. The results show that the three mechanisms provided a decrease in the downtime experienced by the end user where the RTT-based algorithm had the lowest increase in performance and the immediate-throughput-based proposal had the highest increase. The multi-attribute mechanism; while not top performing in terms of less downtime, significantly reduced the amount of time it took to select the new network and thus provides better end user experience

Evaluation of land suitability methods with reference to neglected and underutilised crop species: A scoping review

In agriculture, land use and land classification address questions such as “where”, “why” and “when” a particular crop is grown within a particular agroecology. To date, there are several land suitability analysis (LSA) methods, but there is no consensus on the best method for crop suitability analysis. We conducted a scoping review to evaluate methodological strategies for LSA. Secondary to this, we assessed which of these would be suitable for neglected and underutilised crop species (NUS). The review classified LSA methods reported in articles as traditional (26.6%) and modern (63.4%). Modern approaches, including multi-criteria decision-making (MCDM) methods such as analytical hierarchy process (AHP) (14.9%) and fuzzy methods (12.9%); crop simulation models (9.9%) and machine learning related methods (25.7%) are gaining popularity over traditional methods. The MCDM methods, namely AHP and fuzzy, are commonly applied to LSA while crop models and machine learning related methods are gaining popularity. A total of 67 parameters from climatic, hydrology, soil, socio-economic and landscape properties are essential in LSA. Unavailability and the inclusion of categorical datasets from social sources is a challenge