Dmitri Botvich

Waterford Institute of Technology, Waterford, Munster, Ireland

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Publications (104)38.79 Total impact

  • Ahmed M. Elmisery · Seungmin Rho · Dmitri Botvich
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    ABSTRACT: In our connected world, recommender services have become widely known for their ability to provide expert and personalize information to participants of diverse applications. The excessive growth of social networks, a new kind of services are being embraced which are termed as “group based recommendation services”, where recommender services can be utilized to discover sub-communities within implicit social groups and provide referrals to new participants in order to join various sub-communities of other participants who share similar preferences or interests. Nevertheless, protecting participants’ privacy in recommendation services is a quite crucial aspect which might prevent participants from exchanging their own data with these services, which in turn detain the accuracy of the generated referrals. So in order to gain accurate referrals, recommendation services should have the ability to discover previously unknown sub-communities from different social groups in a way to preserve privacy of participants in each group. In this paper, we present a middleware that runs on end-users’ mobile phones to sanitize their profiles’ data when released for generating referrals, such that computation of referrals continues over the sanitized version of their profiles’ data. The proposed middleware is equipped with cryptography protocols to facilitate private discovery of sub-communities from the sanitized version of participants’ profiles in a university scenario. Location data are added to participants’ profiles to improve the awareness of surrounding sub-communities, so the offered referrals can be filtered based on adjacent locations for participant’s location. We performed a number of different experiments to test the efficiency and accuracy of our protocols. We also developed a formal model for the tradeoff between privacy level and accuracy of referrals. As supported by the experiments, the sub-communities were correctly identified with good accuracy and an acceptable privacy level.
    No preview · Article · Dec 2015 · The Journal of Supercomputing
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    Ahmed M. Elmisery · Seungmin Rho · Dmitri Botvich
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    ABSTRACT: Health social networks (HSNs) have become an integral part of healthcare to augment the ability of people to communicate, collaborate, and share information in the healthcare domain despite obstacles of geography and time. Doctors disseminate relevant medical updates in these platforms and patients take into account opinions of strangers when making medical decisions. This paper introduces our efforts to develop a core platform called Distributed Platform for Health Profiles (DPHP) that enables individuals or groups to control their personal health profiles. DPHP stores user’s personal health profiles in a non-proprietary manner which will enable healthcare providers and pharmaceutical companies to reuse these profiles in parallel in order to maximize the effort where users benefit from each usage for their personal health profiles. DPHP also facilitates the selection of appropriate data aggregators and assessing their offered datasets in an autonomous way. Experimental results were described to demonstrate the proposed search model in DPHP. Multiple advantages might arise when healthcare providers utilize DPHP to collect data for various data analysis techniques in order to improve the clinical diagnosis and the efficiency measurement for some medications in treating certain diseases.
    Preview · Article · Sep 2015 · International Journal of Distributed Sensor Networks
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    AhmedM. Elmisery · Seungmin Rho · Dmitri Botvich
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    ABSTRACT: In our connected world, recommender systems have become widely known for their ability to provide expert and personalized referrals to end-users in different domains. The rapid growth of social networks has given a rise to a new kind of systems, which have been termed “social recommender service”. In this context, a software as a service recommender system can be utilized to extract a set of suitable referrals for certain users based on the data collected from the personal profiles of other end-users within a social structure. However, preserving end-users privacy in social recommender services is a very challenging problem that might prevent privacy concerned users from releasing their own profiles’ data or to be forced to release an erroneous data. Thus, both cases can detain the accuracy of extracted referrals. So in order to gain accurate referrals, the social recommender service should have the ability to preserve the privacy of end-users registered in their system. In this paper, we present a middleware that runs on the end-users’ side in order to conceal their profiles data when being released for the recommendation purposes. The computation of recommendation proceeds over this concealed data. The proposed middleware is equipped with a distributed data collection protocol along with two stage concealment process to give the end-users complete control over the privacy of their profiles. We will present an IPTV network scenario along with the proposed middleware. A number of different experiments were performed on real data which was concealed using our two stage concealment process to evaluate the achieved privacy and accuracy of the extracted referrals. As supported by the experiments, the proposed framework maintains the recommendations accuracy with a reasonable privacy level.
    Preview · Article · Sep 2014 · Multimedia Tools and Applications
  • Leigh Griffin · Kieran Ryan · Eamonn de Leastar · Dmitri Botvich

    No preview · Article · Sep 2014 · International Journal of Ambient Computing and Intelligence
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    Hisain Elshaafi · Dmitri Botvich
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    ABSTRACT: In service-oriented environments, service providers orchestrate distributed services from other providers to create new composite enterprise services. A component service can be invoked jointly by several distributed composite service providers. However, because a composite service is provided to the consumers as an integrated service, when failures or dissatisfaction of the consumers occurs, it is not possible to directly identify the untrustworthy component. In this paper, we describe a collaborative trustworthiness determination approach using optimisation that can provide a solution to selecting trustworthy component service constructs based on monitoring and consumer quality of experience reporting of existing composite services from peer providers.
    Full-text · Article · Mar 2014 · Security and Communication Networks
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    Ahmed M Elmisery · Seungmin Rho · Dmitri Botvich
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    ABSTRACT: Nowadays, it is crucial to preserve the privacy of end-users while utilizing a third-party recommender service within content distribution networks so as to maintain their satisfaction and trust in the offered services. The current business model for those recommender services is centered around the availability of users' personal data at their side whereas consumers have to trust that the recommender service providers will not use their data in a malicious way. With the increasing number of cases for privacy breaches of personal information, different countries and corporations have issued privacy laws and regulations to define the best practices for the protection of personal information. The data protection directive 95/46/EC and the privacy principles established by the Organization for Economic Cooperation and Development (OECD) are examples of such regulation frameworks. In this paper, we assert that utilizing third-party recommender services to generate accurate referrals are feasible, while preserving the privacy of the users' sensitive information which will be residing on a clear form only on his/her own device. As a result, each user who benefits from the third-party recommender service will have absolute control over what to release from his/her own preferences. To support this claim, we proposed a collaborative privacy middleware that executes a two stage concealment process within a distributed data collection protocol in order to attain this claim. Additionally, the proposed solution complies with one of the common privacy regulation frameworks for fair information practice in a natural and functional way -which is OECD privacy principles. The approach presented in this paper is easily integrated into the current business model as it is implemented using a middleware that runs at the end-users side and utilizes the social nature of content distribution services to implement a topological data collection protocol. We depicted how our middleware can be integrated into a scenario related to preserving the privacy of the users' data which is utilized by a third party recommendation service in order to generate accurate referrals for users of mobile jukebox services while maintaining their sensitive information at their own side. Our collaborative privacy framework induces a straightforward solution with accurate results which are beneficial to both users and service providers.
    Full-text · Article · Mar 2014
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    ABSTRACT: The internet is evolving into a full-scale distributed service platform, offering a plethora of services from communications to business, entertainment, social connectivity and much more. The range of services and applications offered is diversifying, with new applications constantly emerging. For example, utility-based computing (e.g. HPC and cloud computing) which relies heavily on data-centre resources. These services will be more dynamic and sophisticated, providing a range of complex capabilities, which puts further burden on data-centres, in terms of supporting and managing these services. At the same time, society is becoming acutely aware of the significant energy burden the communications industry, and in particular data-centres, are becoming. With these trends in mind we propose a biologically inspired service framework that supports services which can autonomously carry out management functions. We then apply this framework to address the emerging problem of a sustainable future internet by autonomously migrating services to greener locations.
    Full-text · Article · Oct 2013 · International Journal of Grid and Utility Computing
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    ABSTRACT: Popularity of IEEE 802.11 networks has increased dramatically over the past number of years. Nowadays audio/video conferencing, gaming and other quality of service (QoS) sensitive services are being delivered to the end users over wireless. Commonly probability for a packet to overstay a specific timeout serves as a QoS metric, and obtaining media access control layer packet delay distribution is highly important for this QoS prediction. Usually wireless devices are equipped with energy supplies of limited capacity, and accurate estimation of their energy expenditure is essential from the network design point of view. Meanwhile, as packets of longer delay normally have higher energy transmission cost, there is a certain dependency between the two metrics. This paper considers internal structure of the metrics and proposes a mathematical model that allows obtaining their individual distributions together with the joint distribution. The model presents a random sum, where the summand formation is determined by a Terminating Markov Process. The model has been validated through comparison with results of NS3 simulation.
    No preview · Article · Jul 2013 · Wireless Networks
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    Dataset: DysonAHP
    Hans Maassen · Dmitri Botvich

    Full-text · Dataset · May 2013
  • Ahmed M. Elmisery · Dmitri Botvich
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    ABSTRACT: This work presents our efforts to design an agent based middleware that enables the end-users to use IPTV content recommender services without revealing their sensitive preference data to the service provider or any third party involved in this process. The proposed middleware (called AMPR) preserves users’ privacy when using the recommender service and permits private sharing of data among different users in the network. The proposed solution relies on a distributed multi-agent architecture involving local agents running on the end-user set up box to implement a two stage concealment process based on user role in order to conceal the local preference data of end-users when they decide to participate in recommendation process. Moreover, AMPR allows the end-users to use P3P policies exchange language (APPEL) for specifying their privacy preferences for the data extracted from their profiles, while the recommender service uses platform for privacy preferences (P3P) policies for specifying their data usage practices. AMPR executes the first stage locally at the end user side but the second stage is done at remote nodes that can be donated by multiple non-colluding end users that we will call super-peers Elmisery and Botvich (2011a, b, c); or third parties mash-up service Elmisery A, Botvich (2011a, b). Participants submit their locally obfuscated profiles anonymously to their local super-peer who collect and mix these preference data from multiple participants. The super-peer invokes AMPR to perform global perturbation process on the aggregated preference data to ensure a complete concealment of user’s profiles. Then, it anonymously submits these aggregated profiles to a third party content recommender service to generate referrals without breaching participants’ privacy. In this paper, we also provide an IPTV network scenario and experimentation results. Our results and analysis shows that our two-stage concealment process not only protect the users’ privacy, but also can maintain the recommendation accuracy
    No preview · Article · May 2013 · Multimedia Tools and Applications
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    David Malone · Hanghang Qi · Dmitri Botvich · Paul Patras
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    ABSTRACT: While there have been considerable advances in the modelling of 802.11's MAC layer in recent years, 802.11 with finite buffer space is considered difficult to analyse. In this paper, we study the impact of finite buffers' effect on the 802.11 performance, in view of the requirements of interactive applications sensitive to delay and packet loss. Using both state-of-the art and simplified queueing models, we identify a surprising result. Specifically, we find that increased buffering throughout an 802.11 network will not only incur delay, but may actually increase the packet loss experienced by stations. By means of numerical analysis and simulations we show that this non-monotonic behaviour arises because of the contention-based nature of the medium access protocol, whose performance is closely related to the traffic load and the buffer size. Finally, we discuss on protocol and buffer tuning towards eliminating such undesirable effect.
    Full-text · Chapter · Jan 2013
  • Hisain Elshaafi · Dmitri Botvich
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    ABSTRACT: This paper presents a novel approach to the inference of trustworthiness of individual components shared between multiple composite services in distributed services environments. In such environments, multiple component services are orchestrated from distributed providers to create new value-added services. A component service can be shared by several distributed compositions. A composite service is offered to its consumers who rate its reliability and satisfaction after each transaction. However, since composite services are provided as an integrated service it is not possible to attribute failures or causes of dissatisfaction to individual components in isolation. A collaborative detection mechanism can provide a solution to the evaluation of component trustworthiness based on consumer reporting of composite service execution results.
    No preview · Article · Jan 2013
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    Hisain Elshaafi · Jimmy Mcgibney · Dmitri Botvich

    Full-text · Conference Paper · Sep 2012
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    Alan Davy · Brendan Jennings · Dmitri Botvich
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    ABSTRACT: In this article we present QoSPlan—a measurement based framework for preparing information relevant to Quality of Service (QoS)-aware IP network planning, which aims at reducing a core operational expenditure for the network operator. QoSPlan is designed to reduce the cost of deployment and maintenance of network monitoring systems. The process involves analysis of pre-existing accounting data to estimate a network-wide traffic matrix. Part of this estimation process relates to the generalization of QoS-related effective bandwidth coefficients taken from traffic analyzed on the network. We offer recommendations on how to appropriately realize QoSPlan to maximize its accuracy and effectiveness when applied to different network traffic scenarios. This is achieved through a thorough sensitivity analysis of the methods proposed using real traffic scenarios and indicative network topologies. We also provide an economic analysis of the deployment and maintenance costs associated with QoSPlan in comparison to a direct measurement approach, demonstrating cost savings of up to 60 % given different topology sizes.
    Full-text · Article · Sep 2012 · Journal of Network and Systems Management
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    ABSTRACT: Wireless body area networks (WBAN) provide a tremendous opportunity for remote health monitoring. However, engineering WBAN health monitoring systems encounters a number of challenges including efficient WBAN monitoring information extraction, dynamically fine tuning the monitoring process to suit the quality of data, and to allow the translation of high-level requirements of medical officers to low-level sensor reconfiguration. This paper addresses these challenges, by proposing an architecture that allows virtual groups to be formed between devices of patients, nurses, and doctors in order to enable remote analysis of WBAN data. Group formation and modification is performed with respect to patients' conditions and medical officers' requirements, which could be easily adjusted through high-level policies. We also propose, a new metric called the Quality of Health Monitoring, which allows medical officers to provide feedback on the quality of WBAN data received. The WBAN data gathered are transmitted to the virtual group members through an underlying environmental sensor network. The proposed approach is evaluated through a series of simulation.
    Full-text · Article · Jul 2012 · IEEE transactions on bio-medical engineering
  • Dmitri Botvich
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    ABSTRACT: This paper presents an approach to monitoring and predicting the trustworthiness of services that are assembled from component services. In service compositions the number of component services that need to be aggregated may be large and dynamically changing. Additionally, the component services may vary in their importance to the value of the composite service and in their trustworthiness and resource capacity. Service compositions require the capability to dynamically adapt to changes that may occur at runtime. Those changes can occur in supply and demand, in the environment or in the component services' properties and behaviour. Service composers need to be able to respond swiftly to changed trustworthiness requirements and capabilities of service compositions, where those changes may not be easily predictable. With the availability of alternatives providing the same functionality as those already integrated in a composition, service composers can take advantage of this by replacing degrading or unsatisfactory components.
    No preview · Conference Paper · Jul 2012
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    ABSTRACT: Wireless Body Area Network (WBAN) in recent years have received significant attention, due to their potential for increasing efficiency in healthcare monitoring. Typical sensors used for WBAN are low powered single transceiver devices utilizing a single channel for transmission at the Medium Access Control (MAC) layer. However, performance of these devices usually degrades when the density of sensors increases. One approach to counter this performance degradation is to exploit multiple channels at the MAC layer, where optimal usage of the channels is achieved through cooperation between the sensor nodes. In this paper we propose a cooperative WBAN environment that supports multi-hop transmission through cooperation involving both environmental sensors and WBAN nodes. Our solution extends the cooperation at the MAC layer to a cross-layered gradient based routing solution that allows interaction between WBAN and environmental sensors in order to ensure data delivery from WBANs to a distant gateway. Extensive simulations for healthcare scenarios have been performed to validate the cooperation at the MAC layer, as well as the cross-layered gradient based routing. Comparisons to other cooperative multi-channel MAC and routing solutions have shown the overall performance improvement of the proposed approach evaluated in terms of packet loss, power consumption and delay.
    Full-text · Article · May 2012 · IEEE Transactions on Consumer Electronics
  • Hisain Elshaafi · Dmitri Botvich

    No preview · Conference Paper · Jan 2012
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    ABSTRACT: The ICT industry is quickly becoming a very significant consumer of global energy. This energy usage clearly comes at an environmental cost, and recent reports estimate that the industry now contributes 2% of the worlds CO2 emissions, or as much as the aviation industry. A significant part of this energy consumption can be attributed to data-centres, where huge numbers of energy-intensive servers host a variety of internet services. Much of this energy consumption is driven by the popularity of the Internet, which continues to attract growing numbers of users who now rely on the Internet as part of their daily lives. A major factor behind this attraction is the multitude of services available on the Internet, ranging from web based services (e.g. facebook) to heavy power consuming services such as multimedia (e.g. youtube, IPTV). As a result of this increased energy usage, the research community has become focused on finding solutions to improve the energy efficiency and carbon footprint of data centres. In this paper we present our solution for delivering green data centres. We propose a Genetic Algorithm-based solution for determining the optimal placement of services in data-centre network, in order to maximize the overall renewable energy usage and minimize the cooling energy consumption. We then perform a series of experiments in order to evaluate our solution, incorporating varying service request profiles and actual weather and renewable energy production values.
    Full-text · Article · Jan 2012
  • Ahmed M. Elmisery · Kevin Doolin · Dmitri Botvich
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    ABSTRACT: With the rapid growth of social networks and users communities the need to attain privacy for end-users becomes mandatory especially with the recent privacy breaches and the inefficiency of anonymisation techniques [1]. The problem of maintaining privacy in recommender services become increasingly important since it aims at finding information that might be interesting to end-users without disclosing their real interests to the service. In this paper, we present a middleware that runs in end-users' mobile phones to provide referrals for joining different sub-communities in conferences or exhibitions in private way. Moreover, the proposed middleware facilitates identifying similarity between various attendees in order to build a community with specific interest without disclosing their real preferences or interests to other parties. Our proposed middleware equipped with two cryptography protocols in order to achieve this purpose. In such case, the attendees can submit their preferences in an encrypted form and the further computation of recommendation proceeds over the encrypted data using secure multiparty computation protocols. We also provide a scenario for community based recommender service for conferences along with experimentation results. Our results shows that our proposed middleware not only protect the attendees' privacy, but also can maintain the recommendation accuracy.
    No preview · Chapter · Jan 2012