The telecommunication market is growing at a very fast pace with the evolution of new technologies to support high speed throughput and the availability of a wide range of services and applications in the mobile networks. This has led to a need for communication service providers (CSPs) to shift their focus from network elements monitoring towards services monitoring and subscribers’ satisfaction by introducing the service quality management (SQM) and the customer experience management (CEM) that require fast responses to reduce the time to find and solve network problems, to ensure efficiency and proactive maintenance, to improve the quality of service (QoS) and the quality of experience (QoE) of the subscribers. While both the SQM and the CEM demand multiple information from different interfaces, managing multiple data sources adds an extra layer of complexity with the collection of data. While several studies and researches have been conducted for data analytics in mobile networks, most of them did not consider analytics based on the four dimensions involved in the mobile networks environment which are the subscriber, the handset, the service and the network element with multiple interface correlation. The main objective of this research was to develop mobile network analytics models applied to the 3G packet-switched domain by analysing data from the radio network with the Iub interface and the core network with the Gn interface to provide a fast root cause analysis (RCA) approach considering the four dimensions involved in the mobile networks. This was achieved by using the latest computer engineering advancements which are Big Data platforms and data mining techniques through machine learning algorithms. / Electrical and Mining Engineering / M. Tech. (Electrical Engineering)

This research study focuses on the application models of Data Mining and Machine Learning covering cellular network traffic, in the objective to arm Mobile Network Operators with full view of performance branches (Services, Device, Subscribers). The purpose is to optimize and minimize the time to detect service and subscriber patterns behaviour. Different data mining techniques and predictive algorithms have been applied on real cellular network datasets to uncover different data usage patterns using specific Key Performance Indicators (KPIs) and Key Quality Indicators (KQI). The following tools will be used to develop the concept: RStudio for Machine Learning and process visualization, Apache Spark, SparkSQL for data and big data processing and clicData for service Visualization. Two use cases have been studied during this research. In the first study, the process of Data and predictive Analytics are fully applied in the field of Telecommunications to efficiently address users’ experience, in the goal of increasing customer loyalty and decreasing churn or customer attrition. Using real cellular network transactions, prediction analytics are used to predict customers who are likely to churn, which can result in revenue loss. Prediction algorithms and models including Classification Tree, Random Forest, Neural Networks and Gradient boosting have been used with an exploratory Data Analysis, determining relationship between predicting variables. The data is segmented in to two, a training set to train the model and a testing set to test the model. The evaluation of the best performing model is based on the prediction accuracy, sensitivity, specificity and the Confusion Matrix on the test set. The second use case analyses Service Quality Management using modern data mining techniques and the advantages of in-memory big data processing with Apache Spark and SparkSQL to save cost on tool investment; thus, a low-cost Service Quality Management model is proposed and analyzed. With increase in Smart phone adoption, access to mobile internet services, applications such as streaming, interactive chats require a certain service level to ensure customer satisfaction. As a result, an SQM framework is developed with Service Quality Index (SQI) and Key Performance Index (KPI). The research concludes with recommendations and future studies around modern technology applications in Telecommunications including Internet of Things (IoT), Cloud and recommender systems. / Cellular networks have evolved and are still evolving, from traditional GSM (Global System for Mobile Communication) Circuit switched which only supported voice services and extremely low data rate, to LTE all Packet networks accommodating high speed data used for various service applications such as video streaming, video conferencing, heavy torrent download; and for say in a near future the roll-out of the Fifth generation (5G) cellular networks, intended to support complex technologies such as IoT (Internet of Things), High Definition video streaming and projected to cater massive amount of data. With high demand on network services and easy access to mobile phones, billions of transactions are performed by subscribers. The transactions appear in the form of SMSs, Handovers, voice calls, web browsing activities, video and audio streaming, heavy downloads and uploads. Nevertheless, the stormy growth in data traffic and the high requirements of new services introduce bigger challenges to Mobile Network Operators (NMOs) in analysing the big data traffic flowing in the network. Therefore, Quality of Service (QoS) and Quality of Experience (QoE) turn in to a challenge. Inefficiency in mining, analysing data and applying predictive intelligence on network traffic can produce high rate of unhappy customers or subscribers, loss on revenue and negative services’ perspective. Researchers and Service Providers are investing in Data mining, Machine Learning and AI (Artificial Intelligence) methods to manage services and experience. This research study focuses on the application models of Data Mining and Machine Learning covering network traffic, in the objective to arm Mobile Network Operators with full view of performance branches (Services, Device, Subscribers). The purpose is to optimize and minimize the time to detect service and subscriber patterns behaviour. Different data mining techniques and predictive algorithms will be applied on cellular network datasets to uncover different data usage patterns using specific Key Performance Indicators (KPIs) and Key Quality Indicators (KQI). The following tools will be used to develop the concept: R-Studio for Machine Learning, Apache Spark, SparkSQL for data processing and clicData for Visualization. / Electrical and Mining Engineering / M. Tech (Electrical Engineering)

A l’avenir, l'agriculture et l'environnement vont pouvoir bénéficier de plus en plus de données hétérogènes collectées par des réseaux de capteurs sans fil (RCSF). Ces données alimentent généralement des outils d’aide à la décision (OAD). Dans cette thèse, nous nous intéressons spécifiquement aux systèmes sensibles et adaptatifs au contexte basés sur un RCSF et un OAD, dédiés au suivi de phénomènes naturels. Nous proposons ainsi une formalisation pour la conception et la mise en œuvre de ces systèmes. Le contexte considéré se compose de données issues du phénomène étudié mais également des capteurs sans fil (leur niveau d’énergie par exemple). Par l’utilisation des ontologies et de techniques de raisonnement, nous visons à maintenir le niveau de qualité de service (QdS) des données collectées (en accord avec le phénomène étudié) tant en préservant le fonctionnement du RCSF. Pour illustrer notre proposition, un cas d'utilisation complexe, l'étude des inondations dans un bassin hydrographique, est considéré. Cette thèse a produit un logiciel de simulation de ces systèmes qui intègre un système de simulation multi-agents (JADE) avec un moteur d’inférence à base de règles (Jess). / In the future, agriculture and environment will rely on more and more heterogeneous data collected by wireless sensor networks (WSN). These data are generally used in decision support systems (DSS). In this dissertation, we focus on adaptive context-aware systems based on WSN and DSS, dedicated to the monitoring of natural phenomena. Thus, a formalization for the design and the deployment of these kinds of systems is proposed. The considered context is established using the data from the studied phenomenon but also from the wireless sensors (e.g., their energy level). By the use of ontologies and reasoning techniques, we aim to maintain the required quality of service (QoS) level of the collected data (according to the studied phenomenon) while preserving the resources of the WSN. To illustrate our proposal, a complex use case, the study of floods in a watershed, is described. During this PhD thesis, a simulator for context-aware systems which integrates a multi-agent system (JADE) and a rule engine (Jess) has been developed.Keywords: ontologies, rule-based inferences, formalization, heterogeneous data, sensors data streams integration, WSN, limited resources, DSS, adaptive context-aware systems, QoS, agriculture, environment.

本論文針對隨機數位網路提出一套可行的計算機制，以提供網路管理者進行資源分配與壅塞管理的分析工具。我們研究兩種利潤最佳化模型，探討在預算控制下的頻寬分配方式。因為資源有限，網路管理者無法隨時提供足夠頻寬以滿足隨機的網路需求，而量測網路連結成功與否的阻塞機率(Blocking Probability)為評估此風險之一種指標。我們利用頻寬分配、網路需求量和虛擬端對端路徑的數量等變數，推導阻塞機率函數，並證明阻塞機率的單調性(Monotonicity)和凸性(Convexity)等數學性質。在不失一般性之假設下，我們驗證阻塞機率是(1)隨頻寬增加而變小；(2)在特定的頻寬分配區間內呈凸性；(3)隨網路需求量增加而變大；(4)隨虛擬路徑的數量增加而變小。 本研究探討頻寬分配與阻塞機率之關係，藉由推導單調性和凸性等性質，提供此兩種利潤模型解的最適條件與求解演算法。同時，我們引用經濟學的彈性概念，提出三種模型參數對阻塞機率變化量的彈性定義，並分別進行頻寬分配、網路需求量和虛擬路徑數量對邊際利潤函數的敏感度分析。當網路上的虛擬路徑數量非常大時，阻塞機率的計算將變得複雜難解，因此我們利用高負荷極限理論(Heavy-Traffic Limit Theorem)提供阻塞機率的估計式，並分析其漸近行為(Asymptotic Behavior)。本論文的主要貢獻是分析頻寬分配與阻塞機率之間的關係及其數學性質。網路管理者可應用本研究提出的分析工具，在總預算限制下規劃寬頻網路的資源分配，並根據阻塞機率進行網路參數的調控。 / This thesis considers the problem of bandwidth allocation on communication networks with multiple traffic classes, where bandwidth is determined under the budget constraint. Due to the limited budget, there exists a risk that the network service providers can not assert a 100% guaranteed availability for the stochastic traffic demand at all times. We derive the blocking probabilities of connections as a function of bandwidth, traffic demand and the available number of virtual end-to-end paths for all service classes. Under general assumptions, we prove that the blocking probability is directionally (i) decreasing in bandwidth, (ii) convex in bandwidth for specific regions, (iii) increasing in traffic demand, and (iv) decreasing in the number of virtual paths. We also demonstrate the monotone and convex relations among those model parameters and the expected path occupancy. As the number of virtual paths is huge, we derive a heavy-traffic queueing model, and provide a diffusion approximation and its asymptotic analysis for the blocking probability, where the traffic intensity increases to one from below. Taking the blocking probability into account, two revenue management schemes are introduced to allocate bandwidth under budget control. The revenue/profit functions are studied in this thesis through the monotonicity and convexity of the blocking probability and expected path occupancy. Optimality conditions are derived to obtain an optimal bandwidth allocation for two revenue management schemes, and a solution algorithm is developed to allocate limited budget among competing traffic classes. In addition, we present three elasticities of the blocking probability to study the effect of changing model parameters on the average revenue in analysis of economic models. The sensitivity analysis and economic elasticity notions are proposed to investigate the marginal revenue for a given traffic class by changing bandwidth, traffic demand and the number of virtual paths, respectively. The main contribution of the present work is to prove the relationship between the blocking probability and allocated bandwidth under the budget constraint. Those results are also verified with numerical examples interpreting the blocking probability, utilization level, average revenue, etc. The relationship between blocking probability and bandwidth allocation can be applied in the design and provision of broadband communication networks by optimally choosing model parameters under budget control for sharing bandwidth in terms of blocking/congestion costs.

Multiple-input, multiple-output (MIMO) techniques have been proposed to meet the needs for higher data rates and lower delays in future wireless communication systems. The downlink capacity of multiuser MIMO systems is achieved when the system transmits to several users simultaneously. Frequently, many more users request service than the transmitter can simultaneously support. Thus, the transmitter requires a scheduling algorithm for the users, which must balance the goals of increasing throughput, reducing multiuser interference, lowering delays, ensuring fairness and quality of service (QoS), etc. In this thesis, we investigate the application of genetic algorithms (GAs) to perform scheduling in multiuser MIMO systems. GAs are a fast, suboptimal, low-complexity method of solving optimization problems, such as the maximization of a scheduling metric, and can handle arbitrary functions and QoS constraints. We first examine a system that transmits using capacity-achieving dirty paper coding (DPC). Our proposed GA structure both selects users and determines their encoding order for DPC, which affects the rates they receive. Our GA can also schedule users independently on different carriers of a multi-carrier system. We demonstrate that the GA performance is close to that of an optimal exhaustive search, but at a greatly reduced complexity. We further show that the GA convergence time can be significantly reduced by tuning the values of its parameters. While DPC is capacity-achieving, it is also very complex. Thus, we also investigate GA scheduling with two linear precoding schemes, block diagonalization and successive zero-forcing. We compare the complexity and performance of the GA with "greedy" scheduling algorithms, and find the GA is more complex, but performs better at higher signal-to-noise ratios (SNRs) and smaller user pool sizes. Both algorithms are near-optimal, yet much less complex than an exhaustive search. We also propose hybrid greedy-genetic algorithms to gain benefits from both types of algorithms. Lastly, we propose an improved method of optimizing the transmit covariance matrices for successive zero-forcing. Our algorithm significantly improves upon the performance of the existing method at medium to high SNRs, and, unlike the existing method, can maximize a weighted sum rate, which is important for fairness and QoS considerations. / Communications

No description available.

The rapid emergence of broadband, or always-on Internet, during the course of the last decade, has increased the importance of the so- called information society in urban and industrialized societies world- wide. Liberalized information and communications technology (ICT) market forces worldwide have however failed to supply these services to rural and low-income regions resulting in the so-called digital divide. One financial tool, adopted by many developing nations to drive broadband investments in underserved areas, is the universal service fund (USF), a public fund mainly levying its resources from ICT market players. USFs have previously been used to fund telecom networks but with the growing importance of broadband, structural and regulatory discrepancies are preventing USFs from adequately supporting broadband investments. Currently, little up-to-date academic theory exists within this field; thus, this thesis serves to outline principles that policy-makers and regulators need to consider when designing or reforming universal service fund mechanisms. The research is based on a series of qualitative country case studies investigating policy, procedural, and executional aspects related to USFs and rural broadband. Publicly available material has been complemented with interviews of stakeholders from various levels to establish a holistic empirical base upon which conclusions have been drawn. The conclusions outline principles governing public involvement in USFs, roles played by various stakeholders in the broadband ecosystem, and strategies for rural broadband network deployment. / Framfarten av bredband under det senaste årtiondet har ökat vikten av det så kallade informationssamhället i de industrialiserade och urbaniserade samhällen. Marknadskrafterna inom den liberaliserade informations- och kommunikationsindustrin har dock misslyckats med att göra dess tjänster tillgängliga till glesbefolkade och låginkomstregioner, vilket har lett till en digital klyfta. Ett finansiellt hjälpmedel som många utvecklingsländer har anammat för att påskynda bredbandsinvesteringar i regioner med få bredbandsuppkopplingar är fonder för samhällsomfattande tjänster (USF), som är en offentlig fond vilken får den största delen av sitt kapital genom en pålaga på intäkterna från aktörer inom informations- och kommunikationsindustrin. USF:er har tidigare använts för att finansiera telekomnätverk, men i takt med att bredbandets ökande genomslag i samhället har strukturella och regleringsmässiga problem med USF:erna uppdagats vilka hindrar dem från att effektivt stödja bredbandsinvesteringar. För närvarande finns lite akademisk teori på området, och sålunda syftar denna uppsatts till att tillhandahålla principer vilka beslutsfattare och regulatorer bör efterfölja vid utformning eller reformering av mekanismer för samhällsomfattande tjänster för bredband. Arbetet baseras på en serie kvalitativa fallstudier av länder med policy, procedurella och verkställande aspekter kopplade till USF:er i områden med få bredbandsuppkopplingar i fokus. Material tillgängligt för allmänheten har kompletterats med intervjuer av intressenter från olika organisations- och samhällsnivåer för att skapa en heltäckande empiri på området från vilka slutsatser har dragits. Slutsatserna innehåller principer som rör offentlig inblandning i USF:er, roller för samhällets olika intressenter i ett ekosystem för bredband, samt strategier för utbyggnad av bredbandsnätverk i glesbefolkade områden.

In IEEE 802.11 WLANs, Link Adaptation mechanisms, which choose the transmission rate of each node, provoke unexpected and random variations on the effective channel capacity. When these changes are towards lower bitrates, inelastic flows, such as VoIP, can suffer from sudden congestion, which results on higher packet delays and losses. In this thesis, a VoIP codec adaptation algorithm is proposed as a solution, based on a cross-layer feedback from RTCP packets and the MAC layer, which can adapt the codecs of active calls to adjust them to the multirate scenario. A combination of this algorithm with a call admission control mechanism is also studied. The results show an important improvement in terms of the QoS of the already active flows as also in the total hotspot's capacity. Additionally, by defining a new Grade of Service related parameter, the Q-Factor, which captures the trade-off between dropping and blocking ratio and perceived speech quality, the codec adaptation algorithm can be tuned to achieve maximum capacity without severely penalizing any of those variables, and hence satisfying both technical and user quality requirements. Finally, a new QoS-enabled AP, which implements these enhancements is designed. / En las redes inalámbricas del estándar IEEE 802.11, los mecanismos de adaptación de enlace que eligen la tasa de transmisión de cada nodo, pueden provocar variaciones aleatorias e inesperadas en la capacidad efectiva del canal. Cuando estos cambios son hacia tasas de transmisión mas bajas, los flujos inelásticos, tales como los de VoIP, pueden de repente sufrir congestión, lo que se traduce en aumento de retrasos y pérdidas de paquetes. En esa tesis, se propone un algoritmo de adaptación de codificadores de voz como solución, basado en técnicas multinivel (cross-layer) que combinan el uso de información de diferentes capas, como los paquetes RTCP y la capa MAC, y que puede adaptar los codecs de las llamadas activas para ajustarlos al escenario "multi-rate". Adicionalmente, la combinación de este algoritmo con un mecanismo de control de admisión de llamadas (CAC) se ha estudiado. Los resultados muestran una importante mejora en términos de QoS de los flujos activos como también en la capacidad total del hotspot. Además, mediante la definición de un nuevo factor, el Q-Factor, que puede captar la compensación entre la tasa de corte y de bloqueo de llamadas y de la calidad percibida por esas, el algoritmo de adaptación de codecs se puede ajustar para lograr la máxima capacidad sin penalizar severamente ninguna de esas variables y así satisfacer los requisitos técnicos de calidad y los usuarios. Por último, un nuevo punto de acceso (AP) habilitado para ofrecer calidad de servicio, ha sido diseñado que lleva a cabo estas mejoras.

Οι οικονομικές και τεχνολογικές εξελίξεις των τελευταίων ετών, η απελευθέρωση της αγοράς, οι ισχυρές κατά απαίτηση πολυμεσικές υπηρεσίες καθώς και ο αυξημένος αριθμός χρηστών των κινητών δικτύων υποδεικνύουν την αναγκαιότητα της σύγκλισης των δύο δικτυακών τεχνολογιών (κινητή τηλεφωνία και internet) με στόχο την παροχή υπηρεσιών Internet στο περιβάλλον των κινητών επικοινωνιών. Η παραπάνω απαίτηση οδήγησε στην δημιουργία του δικτύου επόμενης γενιάς NGN. Η διπλωματική αυτή εργασία ασχολείται με την μελέτη της αρχιτεκτονικής του επιπέδου υπηρεσιών και την υποστήριξη Ποιότητας Υπηρεσίας (QoS) σε δίκτυα Νέας Γενιάς. Συγκεκριμένα δίνεται έμφαση στις λειτουργίες ελέγχου, σηματοδοσίας και λειτουργιών αρχιτεκτονικής του QoS σε επίπεδο υπηρεσιών. Αρχικά, ορίζουμε την έννοια “QoS” όσον αφορά την οπτική του δικτύου και το χρήστη. Περιγράφονται η αρχιτεκτονική του στρώματος υπηρεσιών του δικτύου καθώς και οι λειτουργίες ελέγχου πόρου και αποδοχής των κλήσεων, που αποτελούν σημαντικό μέρος της αρχιτεκτονικής του NGN. Στη συνέχεια παρουσιάζονται αρχιτεκτονικές που προορίζονται για την παροχή του QoS (IntServ, DiffServ), στη Συμφωνία Στάθμης Παρεχόμενης Υπηρεσίας (SLA), το πρωτόκολλο σηματοδοσίας COPS. Επίσης, δίνουμε έμφαση σε ορισμένες πτυχές (χρονοδρομολόγηση, διαχείριση ουρών) μίας QoS αρχιτεκτονικής, οι οποίες είναι ζωτικής σημασίας όσον αφορά την αποδοτική παροχή Ποιότητας Υπηρεσίας. Στη συνέχεια, με τη χρήση του εργαλείου προσομοίωσης OPNET, διεξάγουμε μια σειρά προσομοιώσεων σε ένα ATM και σε ένα NGN δίκτυο. Τέλος, παραθέτουμε και αναλύουμε τα αποτελέσματα των προαναφερθέντων πειραμάτων. / The concept of an NGN (Next Generation Network) has been introduced to take into consideration the new realities in the telecommunications industry, characterized by factors such as: competition among operators due to ongoing deregulation of markets, explosion of digital traffic, e.g.,increasing use of "the Internet", increasing demand for new multimedia services, increasing demand for a general mobility, convergence of networks and services, etc. This thesis has as subject the architecture of service stratum and presents an overview of standards functions defining the Quality of Service (QoS) in Next Generation Networks (NGNs). Several standards bodies define the QoS control architectures based on their scope of work. Specifically, emphasis is given to control functions, signalling and functional architecture of QoS in service stratum. Firstly, we define the meaning of QoS according to the view of the operator’s network and terminal users. The functional architecture of service stratum and especially the part of resource and admission control functions are described in the main body. Furthermore, architectures as IntServ and DiffServ, SLAs and COPS protocol are used as providers of the QoS. Scheduling and queuing management are necessary to optimize the QoS in NGN networks. In this project, we use OPNET simulator in two scenarios to determine construct and control ATM and NGN networks. Finally, collect the results of the experiments and analyze them.

Network on Chips[1][2][3][4] are critical elements of modern System on Chip(SoC) as well as Chip Multiprocessor(CMP)designs. Network on Chips (NoCs) help manage high complexity of designing large chips by decoupling computation from communication. SoCs and CMPs have a multiplicity of communicating entities like programmable processing elements, hardware acceleration engines, memory blocks as well as off-chip interfaces. With power having become a serious design constraint[5], there is a great need for designing NoC which meets the target communication requirements, while minimizing power using all the tricks available at the architecture, microarchitecture and circuit levels of the de-sign. This thesis presents a holistic, QoS based, power optimal design solution of a NoC inside a CMP taking into account link microarchitecture and processor tile configurations. Guaranteeing QoS by NoCs involves guaranteeing bandwidth and throughput for connections and deterministic latencies in communication paths. Label Switching based Network-on-Chip(LS-NoC) uses a centralized LS-NoC Management framework that engineers traffic into QoS guaranteed routes. LS-NoC uses label switching, enables band-width reservation, allows physical link sharing and leverages advantages of both packet and circuit switching techniques. A flow identification algorithm takes into account band-width available in individual links to establish QoS guaranteed routes. LS-NoC caters to the requirements of streaming applications where communication channels are fixed over the lifetime of the application. The proposed NoC framework inherently supports heterogeneous and ad-hoc SoC designs. A multicast, broadcast capable label switched router for the LS-NoC has been de-signed, verified, synthesized, placed and routed and timing analyzed. A 5 port, 256 bit data bus, 4 bit label router occupies 0.431 mm2 in 130nm and delivers peak band-width of80Gbits/s per link at312.5MHz. LS Router is estimated to consume 43.08 mW. Bandwidth and latency guarantees of LS-NoC have been demonstrated on streaming applications like Hiper LAN/2 and Object Recognition Processor, Constant Bit Rate traffic patterns and video decoder traffic representing Variable Bit Rate traffic. LS-NoC was found to have a competitive figure of merit with state-of-the-art NoCs providing QoS. We envision the use of LS-NoC in general purpose CMPs where applications demand deterministic latencies and hard bandwidth requirements. Design variables for interconnect exploration include wire width, wire spacing, repeater size and spacing, degree of pipelining, supply, threshold voltage, activity and coupling factors. An optimal link configuration in terms of number of pipeline stages for a given length of link and desired operating frequency is arrived at. Optimal configurations of all links in the NoC are identified and a power-performance optimal NoC is presented. We presents a latency, power and performance trade-off study of NoCs using link microarchitecture exploration. The design and implementation of a framework for such a design space exploration study is also presented. We present the trade-off study on NoCs by varying microarchitectural(e.g. pipelining) and circuit level(e.g. frequency and voltage) parameters. A System-C based NoC exploration framework is used to explore impacts of various architectural and microarchitectural level parameters of NoC elements on power and performance of the NoC. The framework enables the designer to choose from a variety of architectural options like topology, routing policy, etc., as well as allows experimentation with various microarchitectural options for the individual links like length, wire width, pitch, pipelining, supply voltage and frequency. The framework also supports a flexible traffic generation and communication model. Latency, power and throughput results using this framework to study a 4x4 CMP are presented. The framework is used to study NoC designs of a CMP using different classes of parallel computing benchmarks[6]. One of the key findings is that the average latency of a link can be reduced by increasing pipeline depth to a certain extent, as it enables link operation at higher link frequencies. Abstract There exists an optimum degree of pipelining which minimizes the energy-delay product of the link. In a 2D Torus when the longest link is pipelined by 4 stages at which point least latency(1.56 times minimum) is achieved and power(40% of max) and throughput (64%of max) are nominal. Using frequency scaling experiments, power variations of up to40%,26.6% and24% can be seen in 2D Torus, Reduced 2D Torus and Tree based NoC between various pipeline configurations to achieve same frequency at constant voltages. Also in some cases, we find that switching to a higher pipelining configuration can actually help reduce power as the links can be designed with smaller repeaters. We also find that the overall performance of the ICNs is determined by the lengths of the links needed to support the communication patterns. Thus the mesh seems to perform the best amongst the three topologies(Mesh, Torus and Folded Torus) considered in case studies. The effects of communication overheads on performance, power and energy of a multiprocessor chip using L1,L2 cache sizes as primary exploration parameters using accurate interconnect, processor, on-chip and off-chip memory modelling are presented. On-chip and off-chip communication times have significant impact on execution time and the energy efficiency of CMPs. Large cache simply larger tile area that result in longer inter-tile communication link lengths and latencies, thus adversely impacting communication time. Smaller caches potentially have higher number of misses and frequent of off-tile communication. Energy efficient tile design is a configuration exploration and trade-off study using different cache sizes and tile areas to identify a power-performance optimal configuration for the CMP. Trade-offs are explored using a detailed, cycle accurate, multicore simulation frame-work which includes superscalar processor cores, cache coherent memory hierarchies, on-chip point-to-point communication networks and detailed interconnect model including pipelining and latency. Sapphire, a detailed multiprocessor execution environment integrating SESC, Ruby and DRAM Sim was used to run applications from the Splash2 benchmark(64KpointFFT).Link latencies are estimated for a16 core CMP simulation on Sapphire. Each tile has a single processor, L1 and L2 caches and a router. Different sizesofL1 andL2lead to different tile clock speeds, tile miss rates and tile area and hence interconnect latency. Simulations across various L1, L2 sizes indicate that the tile configuration that maximizes energy efficiency is related to minimizing communication time. Experiments also indicate different optimal tile configurations for performance, energy and energy efficiency. Clustered interconnection network, communication aware cache bank mapping and thread mapping to physical cores are also explored as potential energy saving solutions. Results indicate that ignoring link latencies can lead to large errors in estimates of program completion times, of up to 17%. Performance optimal configurations are achieved at lower L1 caches and at moderateL2 cache sizes due to higher operating frequencies and smaller link lengths and comparatively lesser communication. Using minimal L1 cache size to operate at the highest frequency may not always be the performance-power optimal choice. Larger L1 sizes, despite a drop in frequency, offer a energy advantage due to lesser communication due to misses. Clustered tile placement experiments for FFT show considerable performance per watt improvement (1.2%). Remapping most accessed L2 banks by a process in the same core or neighbouring cores after communication traffic analysis offers power and performance advantages. Remapped processes and banks in clustered tile placement show a performance per watt improvement of5.25% and energy reductionof2.53%. This suggests that processors could execute a program in multiple modes, for example, minimum energy, maximum performance.