Kamal Deep Singh

Cellular software defined networking: a framework

Todays mobile customers desire to remain connected anywhere, at any time, and using any device. This phenomenon has encouraged mobile network operators to build complex network architectures by incorporating new features and extensions, which are harder to manage and operate. In this article we propose a novel and simplified architecture for mobile networks. The proposed architecture, which we call CSDN (Cellular SDN), leverages software defined networking (SDN) and network functions virtualization (NFV). SDN abstracts the network and separates the control plane from the data plane; NFV decouples logical network functions from the underlying hardware, for dynamic resource orchestration. Furthermore, we argue that dynamic resource orchestration and optimal control need real-time context data analyses to make intelligent decisions. Thus, in the proposed architecture we exploit the capability of the mobile edge networks to gather information related to the network as well as the users. This information can be used to optimize network utilization and application performance, and to enhance the user experience. In addition, the gathered data can be shared with third party service providers, enabling the realization of innovative services.

Core techniques of question answering systems over knowledge bases: a survey

The Semantic Web contains an enormous amount of information in the form of knowledge bases (KB). To make this information available, many question answering (QA) systems over KBs were created in the last years. Building a QA system over KBs is difficult because there are many different challenges to be solved. In order to address these challenges, QA systems generally combine techniques from natural language processing, information retrieval, machine learning and Semantic Web. The aim of this survey is to give an overview of the techniques used in current QA systems over KBs. We present the techniques used by the QA systems which were evaluated on a popular series of benchmarks: Question Answering over Linked Data. Techniques that solve the same task are first grouped together and then described. The advantages and disadvantages are discussed for each technique. This allows a direct comparison of similar techniques. Additionally, we point to techniques that are used over WebQuestions and SimpleQuestions, which are two other popular benchmarks for QA systems.

Trill: A reusable Front-End for QA systems

The Semantic Web contains an enormous amount of information in the form of knowledge bases. To make this information available to end-users many question answering (QA) systems over knowledge bases were created in the last years. Their goal is to enable users to access large amounts of structured data in the Semantic Web by bridging the gap between natural language and formal query languages like SPARQL.

WDAqua-core0: A Question Answering Component for the Research Community

We describe and present a new Question Answering (QA) component that can be easily used by the QA research community.

Dynamic anchor points selection for mobility management in Software Defined Networks

Today consumers want to stay connected to networking services anywhere and at anytime. Managing consumers׳ mobility to ensure session and service continuity in efficient and effective manner is more and more challenging due to the increasing number of mobile devices and their high mobility pattern. Different solutions have been proposed in the literature to tackle this problem. They are based on a single mobility management point, called mobility anchor. Unfortunately, most of these solutions suffer from long packets delivery delay and high overhead ratio. In this work, we propose a new mobility management called Software Defined Mobility Management (SDMM) based on the Software Defined Network (SDN) paradigm. The proposed solution is network based, where the mobility is managed by network entities. In opposite to existing approaches, the anchor point is dynamically selected for each flow by a virtual function implemented at the top of the SDN controller which has a global view of the network. The main advantages of our approach are threefold: first reducing packet delivery delay, second reducing the handover latency and third minimizing the tunneling overhead.

EMCOS: Energy-efficient Mechanism for Multimedia Streaming over Cognitive Radio Sensor Networks

One of the major challenges for multimedia transmission over multimedia WSN (MWSN) in urban environment is the scarcity of spectrum combined with high radio interference. Such environment makes it difficult to ensure high bandwidth, low delay and low packet losses required for real time multimedia streaming applications. We target a scenario of video surveillance in urban environment which not only requires efficiency of spectrum utilization, but also requires energy efficient mechanisms for the battery operated MWSN nodes. In this paper, we propose a new solution for multimedia transmission over WSNs which uses cognitive radio technology for spectrum efficiency and clustering mechanism for energy efficiency. A video streaming solution is proposed that is called “EMCOS: Energy-efficient Mechanism for Multimedia Streaming over Cognitive Radio Sensor Networks”. EMCOS ensures high quality real time multimedia transmission from one or more sources to a given sink, under different spectrum availability conditions, while efficiently using the energy of the MWSN nodes. First, EMCOS clusters the MWSN nodes into different clusters in order to ensure low energy consumption. Additionally for clustering, EMCOS not only takes into consideration the geographic positions, but it also takes into account the actual and the forecast of the channel availability in order to ensure stable clusters. Once the clusters are built, a cluster head is elected for each cluster in a way which preserves the cluster energy by considering the energy utilization of all cluster members. Further, to ensure the content delivery from the source to the sink, a routing/channel selection mechanism is proposed. The channel selection is based on PU activity forecasts to prevent frequent channel switching. Simulations show that our proposal EMCOS outperforms the two existing pioneering mechanisms called SEARCH and SCEEM. EMCOS outperforms them in terms of providing higher video quality, lower end-to-end transmission delay and lower frame loss ratio under varied spectrum conditions.

Clustering in cognitive radio for multimedia streaming over wireless Sensor networks

Streaming over multimedia WSN (MWSN) in urban environment is challenging due to many issues among which spectrum scarcity and high radio interference. Such conditions make it difficult to ensure high bandwidth, low transmission delay and low packet losses required for real time multimedia streaming applications. In this paper, we propose COMUS a COgnitive radio solution for MUltimedia streaming over wireless Sensor networks which uses both cognitive radio technology and clustering mechanism to enhance spectrum and energy efficiency. In COMUS we consider clustering the MWSN nodes into different clusters to ensure low energy consumption. Furthermore, based on the nodes geographical position and the actual and the forecasted channel availability, we aim to ensure stable clusters forming. The multimedia streaming from a particular source node to the sink node, require a physical channel selection to perform the corresponding routing task. Thus, in COMUS we propose an efficient channel selection to prevent frequent channel switching which considers the PU (Primary User) activity forecasts. Our simulation results show that COMUS outperforms the two existing pioneering mechanisms called SEARCH and SCEEM and this in terms of providing higher video quality (PSNR and frame rate), lower end-to-end transmission delay and lower frame loss ratio under varied spectrum conditions.

A Scalable Approach for Computing Semantic Relatedness using Semantic Web Data

Computing semantic relatedness is an essential operation for many natural language processing (NLP) tasks, such as Entity Linking (EL) and Question Answering (QA). It is still challenging to find a scalable approach to compute the semantic relatedness using Semantic Web data. Hence, we present for the first time an approach to pre-compute the semantic relatedness between the instances, relations, and classes of an ontology, such that they can be used in real-time applications.

QoE-based routing algorithms for H.264/SVC video over ad-hoc networks

AbstractMulti-hop relaying combined with scarcity of wireless resources in ad-hoc networks can deteriorate the quality of service. As a result, one of the major challenges in video streaming over ad-hoc networks isn enhancing users’ experience and network utilization. The emergence of scalable video coding standard enables smooth adaptation of video quality to network conditions. In this paper, we study two optimization problems: (1) maximize the global quality of experience of all users and (2) maximize the number of qualified streams. We formulate the both problems as mixed integer linear programming problems. These optimization problems are shown to be NP-hard. Consequently, we propose heuristic algorithms to solve them. Simulation results show that the proposed algorithms can provide the near-optimal video quality while the calculation times are much shorter than the one of optimal solution.

WDAqua-core1: A Question Answering service for RDF Knowledge Bases

In the last two decades a new part of the web grew significantly, namely the Semantic Web. It contains many Knowledge Bases (KB) about different areas like music, books, publications, live science and many more. Question Answering (QA) over KBs is seen as the most promising approach to bring this data to end-users. We describe WDAqua-core1, a QA service for querying RDF knowledge-bases. It is multilingual, it supports different RDF knowledge bases and it understands both full natural language questions and keyword questions.