Burak Kantarci

Health Monitoring and Management Using Internet-of-Things (IoT) Sensing with Cloud-Based Processing: Opportunities and Challenges

Among the panoply of applications enabled by the Internet of Things (IoT), smart and connected health care is a particularly important one. Networked sensors, either worn on the body or embedded in our living environments, make possible the gathering of rich information indicative of our physical and mental health. Captured on a continual basis, aggregated, and effectively mined, such information can bring about a positive transformative change in the health care landscape. In particular, the availability of data at hitherto unimagined scales and temporal longitudes coupled with a new generation of intelligent processing algorithms can: (a) facilitate an evolution in the practice of medicine, from the current post facto diagnose-and-treat reactive paradigm, to a proactive framework for prognosis of diseases at an incipient stage, coupled with prevention, cure, and overall management of health instead of disease, (b) enable personalization of treatment and management options targeted particularly to the specific circumstances and needs of the individual, and (c) help reduce the cost of health care while simultaneously improving outcomes. In this paper, we highlight the opportunities and challenges for IoT in realizing this vision of the future of health care.

Trustworthy Sensing for Public Safety in Cloud-Centric Internet of Things

The Internet of Things (IoT) paradigm stands for virtually interconnected objects that are identifiable and equipped with sensing, computing, and communication capabilities. Implementation of services and applications over the IoT architecture can take benefit of the cloud computing concept. Sensing-as-a-Service (S2 aaS) is a cloud-inspired service model which enables access to the IoT. In this paper, we present a framework where IoT can enhance public safety by crowd management via sensing services that are provided by smart phones equipped with various types of sensors. In order to ensure trustworthiness in the presented framework, we propose a reputation-based (S2 aaS) scheme, namely, Trustworthy Sensing for Crowd Management (TSCM) for front-end access to the IoT. TSCM collects sensing data based on a cloud model and an auction procedure which selects mobile devices for particular sensing tasks and determines the payments to the users of the mobile devices that provide data. Performance evaluation of TSCM shows that the impact of malicious users in the crowdsourced data can be degraded by 75% while trustworthiness of a malicious user converges to a value below 40% following few auctions. Moreover, we show that TSCM can enhance the utility of the public safety authority up to 85%.

Reliable overlay topology design for the smart microgrid network

Integration of the advances in information and communication technologies to the power grid technologies is changing the architecture and operation of the traditional grid, leading the grid to gradually evolve into a smart grid. Generation in the smart grid will be different than it is in todays grid, mainly due to the high penetration level of distributed renewable power generators. The distributed generator (DG) is favorable for its low transmission losses and low emissions. On the other hand, control of a high number of DGs is challenging. Almost a decade ago, microgrids were proposed to tackle the challenge of handling the growing number of DGs and fault isolation. A microgrid is a medium voltage or low voltage electrical power system that contains DGs, storage units, controllable loads, small-scale combined heat and power units, and an energy management system. In this article, we revisit the microgrid concept in light of survivability approaches borrowed from high-speed networks. We provide an analogy between survivability in metroaccess networks and reliability of the overlay topology for the smart microgrid network (SMGN). We develop the idea of resource sharing among smart microgrids for the sake of increased reliability. In our case, reliability corresponds to supplying power to the loads using the energy generated in the SMGN, without importing power from the utility grid. We provide a reliable overlay topology design scheme that maximizes the usage of renewable energy in the SMGN.

Bandwidth Distribution Solutions for Performance Enhancement in Long-Reach Passive Optical Networks

Long-reach Passive Optical Networks (LR-PONs) aim to combine the capacity of metro and access networks by extending the reach and split ratio of the conventional PONs. LR-PONs appear as efficient solutions having feeder distances around 100km and high split ratios up to 1000-way. On the other hand, transmission of the signals in long distances up to 100km leads to increased propagation delay whereas high split ratio may lead to long cycle times resulting in large queue occupancies and long packet delays. Before LR-PON becomes widely adopted, the trade-off between the advantages and performance degradation problem which is resulting from long reach and high split ratio properties of LR-PONs needs to be solved. Recent studies have focused on enhancing the performance of dynamic bandwidth allocation in LR-PONs. This article presents a comprehensive survey on the dynamic bandwidth allocation schemes for LR-PONs. In the article, a comparative classification of the proposed schemes based on their quality-of-service awareness, base-types, feeder distances and tested performance metrics is provided. At the end of the article, a brief discussion on the open issues and research challenges for the solution of performance degradation in LR-PONs is presented.

Cloud-centric multi-level authentication as a service for secure public safety device networks

With the advances in IoT, future public safety responders will be well armed with devices that pump data between on-site responders and command centers, carrying useful information about the event scene, the status of a mission, and helping critical decisions to be made in real time. In addition, wearable and on-body sensors will monitor the vital signals and well being of the responders. These connected devices or the so-called IoT surrounding public safety responders generate highly vulnerable data, where security breaches may have life threatening consequences. Authentication of responder devices is essential in order to control access to public safety networks. Most of the existing authentication schemes do not scale well with the large number of devices of IoT, and are not fast enough to work during time-critical public safety missions. On the other hand, for general IoT services, cloud-based solutions provide unlimited resources for storing and accessing IoT data. However, the cloud may have some implications for sensitive data that are collected for public safety. Therefore, authentication solutions are desired to integrate well into the cloud environment. In this article, we propose cloud-centric, multi-level authentication as a service approach that addresses scalability and time constraints, and demonstrate its effectiveness. We draw future research directions for secure public safety networks in the presence of IoT devices and the cloud.

Energy efficiency in the extended-reach fiber-wireless access networks

Telecommunication networks call for novel energy-efficient design and management schemes as a result of the increasing contribution of the ICT sector to electricity consumption and greenhouse gas emissions. Access networks, being one of the significant contributors in the last mile, require power saving protocols and architectures. As one of the emerging access network solutions, convergence of PONs and wireless access networks, also named as FiWi, offer to combine the robustness and high capacity of optical networks with the mobility and ubiquity of wireless networks. In this article, we present an overview and a brief comparison of energy-efficient protocols and design approaches in FiWi networks. We further propose an energy-efficient bandwidth allocation mechanism in FiWi networks that adopts an optical burst switching (OBS)-like report generation mechanism in LREPON. Through simulations, we show that the proposed scheme leads to significant energy savings in the long-reach FiWi network while overcoming the delay penalty of the ONU-BS sleep modes.

Anchor-Assisted and Vote-Based Trustworthiness Assurance in Smart City Crowdsensing

Smart city sensing calls for crowdsensing via mobile devices that are equipped with various built-in sensors. As incentivizing users to participate in distributed sensing is still an open research issue, the trustworthiness of crowdsensed data is expected to be a grand challenge if this cloud-inspired recruitment of sensing services is to be adopted. Recent research proposes reputation-based user recruitment models for crowdsensing; however, there is no standard way of identifying adversaries in smart city crowdsensing. This paper adopts previously proposed vote-based approaches, and presents a thorough performance study of vote-based trustworthiness with trusted entities that are basically a subset of the participating smartphone users. Those entities are called trustworthy anchors of the crowdsensing system. Thus, an anchor user is fully trustworthy and is fully capable of voting for the trustworthiness of other users, who participate in sensing of the same set of phenomena. Besides the anchors, the reputations of regular users are determined based on vote-based (distributed) reputation. We present a detailed performance study of the anchor-based trustworthiness assurance in smart city crowdsensing through simulations, and compare it with the purely vote-based trustworthiness approach without anchors, and a reputation-unaware crowdsensing approach, where user reputations are discarded. Through simulation findings, we aim at providing specifications regarding the impact of anchor and adversary populations on crowdsensing and user utilities under various environmental settings. We show that significant improvement can be achieved in terms of usefulness and trustworthiness of the crowdsensed data if the size of the anchor population is set properly.

Inter-and-intra data center VM-placement for energy-efficient large-Scale cloud systems

Data centers play the crucial role in the delivery of Cloud services by enabling on-demand access to the shared resources such as software, platform, and infrastructure. Virtual Machine (VM) allocation is one of the challenging tasks in the data center management since user requirements, typically expressed as SLAs, have to be met with the minimum operational expenditure. Despite their huge processing and storage facilities, data centers are among the major contributors of the GreenHouse Gas (GHG) emissions of the IT services. In this paper, we propose a holistic approach for a large-scale Cloud system where the Cloud services are provisioned by several data centers interconnected over the backbone network. We propose a Mixed Integer Linear Programming (MILP) formulation that aims at virtualizing the backbone topology and placing the VMs in data centers with the objective of minimum power consumption. We compare our proposed solution with a benchmark MILP model which selects the closest data centers that can accommodate the user requests taking into account the CPU, memory, and bandwidth capacities of the residing physical hosts. Collected experimental results show the benefit of the proposed management scheme in terms of power consumption, resource utilization, and fairness for medium size data centers.

Energy-Efficient Cloud Services over Wavelength-Routed Optical Transport Networks

Optical WDM networks can be employed as the transport medium technology for cloud computing services since they have high capacity and low delay, and they satisfy the service requirements by the help of the control plane. Recent research has shown that cloud services can be efficiently provisioned based on anycast or manycast paradigms. In this paper, we focus on the energy savings in the optical transport network which forms a communication infrastructure for the cloud services based on the manycast paradigm. We propose an optimization model to maximize the energy savings by putting the wavelength routing modules of the optical nodes in the power saving mode. Based on the optimization model, we propose an evolutionary algorithm, namely the Evolutionary Algorithm for Green Light-tree Establishment (EAGLE) which can provide lower runtime for large topologies and find a suboptimal solution. We evaluate the performance of our optimization model by running EAGLE under a topology lying on four different time zones, i.e., NSFNET. Simulation results verify that selecting a feasible number of nodes to put their wavelength routing modules in the power saving mode leads to significant energy savings in transportation of the cloud services over WDM networks. Furthermore, the proposed scheme does not introduce a resource consumption penalty when compared to the wavelength minimizing approach.

Designing an energy-efficient cloud network [Invited]

Cloud computing services are mainly hosted in remote data centers (DCs) where high performance servers and high capacity storage systems are located. Moving the services to distant servers can help handling the energy bottleneck of the information and communication technologies by leading to significant power savings at the local computing resources, which on the other hand increases the energy consumption of the transport network and the DCs. In this paper, we propose mixed-integer-linear-programming- (MILP-) based provisioning models to guarantee either minimum delayed or maximum power-saving cloud services where high performance DCs are assumed to be located at the core nodes of an IP-over-wavelength division multiplexing network. We further propose heuristics, namely, delay-minimized provisioning and power-minimized provisioning, each of which mimics the behavior of the benchmark MILP formulation. Through numerical results, we show that power savings can be attained at the expense of increased propagation delays. Hence, we finally propose the delay- and power-minimized provisioning (DePoMiP), which aims to minimize the propagation delay, maximize the power savings in the transport network and minimize the power consumption overhead introduced to the DCs. Simulation results verify that DePoMiP achieves low-delay and low-power provisioning in an environment which is dominated by the cloud services.