Identification of femtocells in mobile networks

The evolving mobile networks are requested to convey increasing data traffic as popularity of online services together with affordability of mobile devices is growing. One solution to mobile carriers, which can help them quickly deploy small base stations (BS) ensuring great indoor coverage with minimum costs, and high data rate capability, is femtocell technology. However, standard deployment techniques are unsatisfactory for these type of BSs. There are two main reasons for that. Firstly, femtocells will be deployed in great numbers. Secondly, they are deployed by users and are portable. It means their position is not known in advance, and can vary in time. Therefore, femtocells have to implement self-configuration principles. Physical Cell Identity is one of the most important parameters to be chosen automatically under defined conditions. It is crucial parameter, which allows them to convey a communication between a user equipment and a core network. A study on Physical Cell Identity issues in mobile networks with femtocells is presented in my thesis. For this purpose, I created two different models of femtocells deployment and deal with a collision and a confusion. They are two main problems, which threaten proper Physical Cell Identity assignment in mobile networks. Outputs of the thesis serves for better understanding of interrelations between differently placed femtocells in term of collision and confusion issue and as the basis to design the framework handling Physical Cell Identity allocation. The simulations conducted on proposed models were utilized to obtain probability characteristics and indicators based on graph theory. In the evaluation section, I appoint several characteristics as probability of collision, probability of confusion and maximal number of neighbourhood cells and some others to support solution of collision and confusion issue. I use results of evaluation and layout the framework for automated Physical Cell Identity assignment with two different approaches, the distributed one, and the centralized one. Since, femtocells are subcategory of small cells so findings, mentioned in this thesis, can also be used for other types of small cells.Katedra telekomunikační technik

Formulation, implementation considerations, and first performance evaluation of algorithmic solutions - D4.1

Deliverable D4.1 del projecte Europeu OneFIT (ICT-2009-257385)This deliverable contains a first version of the algorithmic solutions for enabling opportunistic networks. The presented algorithms cover the full range of identified management tasks: suitability, creation, QoS control, reconfiguration and forced terminations. Preliminary evaluations complement the proposed algorithms. Implementation considerations towards the practicality of the considered algorithms are also included.Preprin

A metaheuristic and simheuristic approach for the p-Hub median problem from a telecommunication perspective

Tese (doutorado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2018.Avanços recentes no setor das telecomunicações oferecem grandes oportunidades para cidadãos e organizações em um mundo globalmente conectado, ao mesmo tempo em que surge um vasto número de desafios complexos que os engenheiros devem enfrentar. Alguns desses desafios podem ser modelados como problemas de otimização. Alguns exemplos incluem o problema de alocação de recursos em redes de comunicações, desenho de topologias de rede que satisfaça determinadas propriedades associadas a requisitos de qualidade de serviço, sobreposição de redes multicast e outros recursos importantes para comunicação de origem a destino. O primeiro objetivo desta tese é fornecer uma revisão sobre como as metaheurísticas têm sido usadas até agora para lidar com os problemas de otimização associados aos sistemas de telecomunicações, detectando as principais tendências e desafios. Particularmente, a análise enfoca os problemas de desenho, roteamento e alocação de recursos. Além disso, devido á natureza desses desafios, o presente trabalho discute como a hibridização de metaheurísticas com metodologias como simulação pode ser empregada para ampliar as capacidades das metaheurísticas na resolução de problemas de otimização estocásticos na indústria de telecomunicações. Logo, é analisado um problema de otimização com aplicações práticas para redes de telecomunica ções: o problema das p medianas não capacitado em que um número fixo de hubs tem capacidade ilimitada, cada nó não-hub é alocado para um único hub e o número de hubs é conhecido de antemão, sendo analisado em cenários determinísticos e estocásticos. Dada a sua variedade e importância prática, o problema das p medianas vem sendo aplicado e estudado em vários contextos. Seguidamente, propõem-se dois algoritmos imune-inspirados e uma metaheurística de dois estágios, que se baseia na combinação de técnicas tendenciosas e aleatórias com uma estrutura de busca local iterada, além de sua integração com a técnica de simulação de Monte Carlo para resolver o problema das p medianas. Para demonstrar a eficiência dos algoritmos, uma série de testes computacionais é realizada, utilizando instâncias de grande porte da literatura. Estes resultados contribuem para uma compreensão mais profunda da eficácia das metaheurísticas empregadas para resolver o problema das p medianas em redes pequenas e grandes. Por último, uma aplicaçã o ilustrativa do problema das p medianas é apresentada, bem como alguns insights sobre novas possibilidades para ele, estendendo a metodologia proposta para ambientes da vida real.Recent advances in the telecommunication industry o er great opportunities to citizens and organizations in a globally-connected world, but they also arise a vast number of complex challenges that decision makers must face. Some of these challenges can be modeled as optimization problems. Examples include the framework of network utility maximization for resource allocation in communication networks, nding a network topology that satis es certain properties associated with quality of service requirements, overlay multicast networks, and other important features for source to destination communication. First, this thesis provides a review on how metaheuristics have been used so far to deal with optimization problems associated with telecommunication systems, detecting the main trends and challenges. Particularly the analysis focuses on the network design, routing, and allocation problems. In addition, due to the nature of these challenges, this work discusses how the hybridization of metaheuristics with methodologies such as simulation can be employed to extend the capabilities of metaheuristics when solving stochastic optimization problems. Then, a popular optimization problem with practical applications to the design of telecommunication networks: the Uncapacitated Single Allocation p-Hub Median Problem (USApHMP) where a xed number of hubs have unlimited capacity, each non-hub node is allocated to a single hub and the number of hubs is known in advance is analyzed in deterministic and stochastic scenarios. p-hub median problems are concerned with optimality of telecommunication and transshipment networks, and seek to minimize the cost of transportation or establishing. Next, two immune inspired metaheuristics are proposed to solve the USApHMP, besides that, a two-stage metaheuristic which relies on the combination of biased-randomized techniques with an iterated local search framework and its integration with simulation Monte Carlo technique for solving the same problem is proposed. In order to show their e ciency, a series of computational tests are carried out using small and large size instances from the literature. These results contribute to a deeper understanding of the e ectiveness of the employed metaheuristics for solving the USApHMP in small and large networks. Finally, an illustrative application of the USApHMP is presented as well as some insights about some new possibilities for it, extending the proposed methodology to real-life environments.Els últims avenços en la industria de les telecomunicacions ofereixen grans oportunitats per ciutadans i organitzacions en un món globalment connectat, però a la vegada, presenten reptes als que s'enfronten tècnics i enginyers que prenen decisions. Alguns d'aquests reptes es poden modelitzar com problemes d'optimització. Exemples inclouen l'assignació de recursos a les xarxes de comunicació, trobant una topologia de xarxa que satisfà certes propietats associades a requisits de qualitat de servei, xarxes multicast superposades i altres funcions importants per a la comunicació origen a destinació. El primer objectiu d'aquest treball és proporcionar un revisió de la literatura sobre com s'han utilitzat aquestes tècniques, tradicionalment, per tractar els problemes d'optimització associats a sistemes de telecomunicació, detectant les principals tendències i desa aments. Particularment, l'estudi es centra en els problemes de disseny de xarxes, enrutament i problemes d'assignació de recursos. Degut a la naturalesa d'aquests problemes, aquest treball també analitza com es poden combinar les tècniques metaheurístiques amb metodologies de simulació per ampliar les capacitats de resoldre problemes d'optimització estocàstics. A més, es tracta un popular problema d'optimització amb aplicacions pràctiques per xarxes de telecomunicació, el problema de la p mediana no capacitat, analitzant-lo des d'escenaris deterministes i estocàstics. Aquest problema consisteix en determinar el nombre d'instal lacions (medianes) en una xarxa, minimitzant la suma de tots els costs o distàncies des d'un punt de demanda a la instal lació més propera. En general, el problema de la p mediana està lligat amb l'optimització de xarxes de telecomunicacions i de transport, i busquen minimitzar el cost de transport o establiment de la xarxa. Es proposa dos algoritmes immunològics i un algoritme metaheurístic de dues etapes basat en la combinació de tècniques aleatòries amb simulacions Monte Carlo. L'e ciència de les algoritmes es posa a prova mitjançant alguns dels test computacionals més utilitzats a la literatura, obtenint uns resultats molt satisfactoris, ja que es capaç de resoldre casos petits i grans en qüestió de segons i amb un baix cost computacional. Finalment, es presenta una aplicació il lustrativa del problema de la p mediana, així com algunes noves idees sobre aquest, que estenen la metodologia proposta a problemes de la vida real

A cross-layer approach for optimizing the efficiency of wireless sensor and actor networks

Recent development has lead to the emergence of distributed Wireless Sensor and Actor Networks (WSAN), which are capable of observing the physical environment, processing the data, making decisions based on the observations and performing appropriate actions. WSANs represent an important extension of Wireless Sensor Networks (WSNs) and may comprise a large number of sensor nodes and a smaller number of actor nodes. The sensor nodes are low-cost, low energy, battery powered devices with restricted sensing, computational and wireless communication capabilities. Actor nodes are resource richer with superior processing capabilities, higher transmission powers and a longer battery life. A basic operational scenario of a typical WSAN application follows the following sequence of events. The physical environment is periodically sensed and evaluated by the sensor nodes. The sensed data is then routed towards an actor node. Upon receiving sensed data, an actor node performs an action upon the physical environment if necessary, i.e. if the occurrence of a disturbance or critical event has been detected. The specific characteristics of sensor and actor nodes combined with some stringent application constraints impose unique requirements for WSANs. The fundamental challenges for WSANs are to achieve low latency, high energy efficiency and high reliability. The latency and energy efficiency requirements are in a trade-off relationship. The communication and coordination inside WSANs is managed via a Communication Protocol Stack (CPS) situated on every node. The requirements of low latency and energy efficiency have to be addressed at every layer of the CPS to ensure overall feasibility of the WSAN. Therefore, careful design of protocol layers in the CPS is crucial in attempting to meet the unique requirements and handle the abovementioned trade-off relationship in WSANs. The traditional CPS, comprising the application, network, medium access control and physical layer, is a layered protocol stack with every layer, a predefined functional entity. However, it has been found that for similar types of networks with similar stringent network requirements, the strictly layered protocol stack approach performs at a sub-optimal level with regards to network efficiency. A modern cross-layer paradigm, which proposes the employment of interactions between layers in the CPS, has recently attracted a lot of attention. The cross-layer approach promotes network efficiency optimization and promises considerable performance gains. It is found that in literature, the adoption of this cross-layer paradigm has not yet been considered for WSANs. In this dissertation, a complete cross-layer enabled WSAN CPS is developed that features the adoption of the cross-layer paradigm towards promoting optimization of the network efficiency. The newly proposed cross-layer enabled CPS entails protocols that incorporate information from other layers into their local decisions. Every protocol layer provides information identified as beneficial to another layer(s) in the CPS via a newly proposed Simple Cross-Layer Framework (SCLF) for WSANs. The proposed complete cross-layer enabled WSAN CPS comprises a Cross-Layer enabled Network-Centric Actuation Control with Data Prioritization (CL-NCAC-DP) application layer (APPL) protocol, a Cross-Layer enabled Cluster-based Hierarchical Energy/Latency-Aware Geographic Routing (CL-CHELAGR) network layer (NETL) protocol and a Cross-Layer enabled Carrier Sense Multiple Access with Minimum Preamble Sampling and Duty Cycle Doubling (CL-CSMA-MPS-DCD) medium access control layer (MACL) protocol. Each of these protocols builds on an existing simple layered protocol that was chosen as a basis for development of the cross-layer enabled protocols. It was found that existing protocols focus primarily on energy efficiency to ensure maximum network lifetime. However, most WSAN applications require latency minimization to be considered with the same importance. The cross-layer paradigm provides means of facilitating the optimization of both latency and energy efficiency. Specifically, a solution to the latency versus energy trade-off is given in this dissertation. The data generated by sensor nodes is prioritised by the APPL and depending on the delay-sensitivity, handled in a specialised manor by every layer of the CPS. Delay-sensitive data packets are handled in order to achieve minimum latency. On the other hand, delay-insensitive non critical data packets are handled in such a way as to achieve the highest energy efficiency. In effect, either latency minimization or energy efficiency receives an elevated precedence according to the type of data that is to be handled. Specifically, the cross-layer enabled APPL protocol provides information pertaining to the delay-sensitivity of sensed data packets to the other layers. Consequently, when a data packet is detected as highly delay-sensitive, the cross-layer enabled NETL protocol changes its approach from energy efficient routing along the maximum residual energy path to routing along the fastest path towards the cluster-head actor node for latency minimizing of the specific packet. This is done by considering information (contained in the SCLF neighbourhood table) from the MACL that entails wakeup schedules and channel utilization at neighbour nodes. Among the added criteria, the next-hop node is primarily chosen based on the shortest time to wakeup. The cross-layer enabled MACL in turn employs a priority queue and a temporary duty cycle doubling feature to enable rapid relaying of delay-sensitive data. Duty cycle doubling is employed whenever a sensor node’s APPL state indicates that it is part of a critical event reporting route. When the APPL protocol state (found in the SCLF information pool) indicates that the node is not part of the critical event reporting route anymore, the MACL reverts back to promoting energy efficiency by disengaging duty cycle doubling and re-employing a combination of a very low duty cycle and preamble sampling. The APPL protocol conversely considers the current queue size of the MACL and temporarily halts the creation of data packets (only if the sensed value is non critical) to prevent a queue overflow and ease congestion at the MACL By simulation it was shown that the cross-layer enabled WSAN CPS consistently outperforms the layered CPS for various network conditions. The average end-to-end latency of delay-sensitive critical data packets is decreased substantially. Furthermore, the average end-to-end latency of delay-insensitive data packets is also decreased. Finally, the energy efficiency performance is decreased by a tolerable insignificant minor margin as expected. The trivial increase in energy consumption is overshadowed by the high margin of increase in latency performance for delay-sensitive critical data packets. The newly proposed cross-layer CPS achieves an immense latency performance increase for WSANs, while maintaining excellent energy efficiency. It has hence been shown that the adoption of the cross-layer paradigm by the WSAN CPS proves hugely beneficial with regards to the network efficiency performance. This increases the feasibility of WSANs and promotes its application in more areas.Dissertation (MEng)--University of Pretoria, 2009.Electrical, Electronic and Computer Engineeringunrestricte

A state communication and software switching module and thin middleware layer for reconfiguration management in reconfigurable manufacturing systems.

M. Sc. Eng. University of KwaZulu-Natal, Durban 2015.Reconfigurable Manufacturing Systems are a new area of operations and manufacturing research. The global need for production systems which can react rapidly to dynamic markets has increased in the last decade and will continue to drive changes in the manufacturing industry. The further development of RMS technologies is therefore highly important for future industries. The Reconfiguration Management and Middleware System (RMMS) developed in this research aimed to form a hardware-supported middleware technology which allows for the fast and seamless ramp-up of heterogeneous machine controllers on a newly reconfigured factory floor. The goal was to allow for the autonomous assignment and switching of software routines on machine controllers after a physical reconfiguration, thereby speeding up the ramp-up of the system. The technology was based on a recorded literature review and fits into the paradigm of RMS. The RMMS was developed not as a traditional software-heavy layer, but as a thin layer of software assisted by interactive mechatronic hardware, designed to remove heterogeneity in the control software. The system design was based on research into areas of engineering and operations management and followed the Mechatronic design approach. The literature led to a technology that takes the entire RMS paradigm into account and the development was conducted in conjunction with experiments to verify the individual functionality of each sub-system and ensure the overall system’s success. The RMMS uses hardware to handle heterogeneity and uses a positioning system (developed by the author) along with an intelligent processing system (a clustering algorithm and artificial intelligence engine) to construct data into a factory floor model. The positioning system, when assisted by the intelligence, operates at an accuracy of over 90%, which is comparable to commercial positioning techniques which cost over ten times more. The RMMS used the developed model to, autonomously and wirelessly, assign new programs to machine controllers after a physical reconfiguration, to complete a factory reconfiguration. The system was verified through practical scenarios constructed in the Mechatronics laboratory. Realistic reconfiguration operations were performed and the RMMS was required to detect changes in the factory floor and respond by assigning new, appropriate, software routines to each machine controller in the system. Experiments have proved that the system was capable of re-establishing operations in under half an hour, as opposed to a full day using manual techniques. The system has accurately switched between control routines based on the physical state of the factory floor, which amounts to control reconfiguration. The reconfiguration of factory floor control was successful in four out of four factory layouts tested and therefore successfully does a job no commercially available system can do

LIPIcs, Volume 277, GIScience 2023, Complete Volume

LIPIcs, Volume 277, GIScience 2023, Complete Volum

Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network

In Wireless Sensor Network (WSN), high transmission time occurs when search agent focuses on the same sensor nodes, while local optima problem happens when agent gets trapped in a blind alley during searching. Swarm intelligence algorithms have been applied in solving these problems including the Ant Colony System (ACS) which is one of the ant colony optimization variants. However, ACS suffers from local optima and stagnation problems in medium and large sized environments due to an ineffective exploration mechanism. This research proposes a hybridization of Enhanced ACS and Tabu Search (EACS(TS)) algorithm for packet routing in WSN. The EACS(TS) selects sensor nodes with high pheromone values which are calculated based on the residual energy and current pheromone value of each sensor node. Local optima is prevented by marking the node that has no potential neighbour node as a Tabu node and storing it in the Tabu list. Local pheromone update is performed to encourage exploration to other potential sensor nodes while global pheromone update is applied to encourage the exploitation of optimal sensor nodes. Experiments were performed in a simulated WSN environment supported by a Routing Modelling Application Simulation Environment (RMASE) framework to evaluate the performance of EACS(TS). A total of 6 datasets were deployed to evaluate the effectiveness of the proposed algorithm. Results showed that EACS(TS) outperformed in terms of success rate, packet loss, latency, and energy efficiency when compared with single swarm intelligence routing algorithms which are Energy-Efficient Ant-Based Routing (EEABR), BeeSensor and Termite-hill. Better performances were also achieved for success rate, throughput, and latency when compared to other hybrid routing algorithms such as Fish Swarm Ant Colony Optimization (FSACO), Cuckoo Search-based Clustering Algorithm (ICSCA), and BeeSensor-C. The outcome of this research contributes an optimized routing algorithm for WSN. This will lead to a better quality of service and minimum energy utilization