arXiv subjects

Kin K. Leung

Publications and source records attributed to Kin K. Leung.

62 records · Page 4Linked to original sources

arXiv2017

Live Service Migration in Mobile Edge Clouds

Mobile edge clouds (MECs) bring the benefits of the cloud closer to the user, by installing small cloud infrastructures at the network edge. This enables a new breed of real-time applications, such as instantaneous object recognition and safety assistance in intelligent transportation systems, that require very low latency. One key issue that comes with proximity is how to ensure that users always receive good performance as they move across different locations. Migrating services between MECs is seen as the means to achieve this. This article presents a layered framework for migrating active service applications that are encapsulated either in virtual machines (VMs) or containers. This layering approach allows a substantial reduction in service downtime. The framework is easy to implement using readily available technologies, and one of its key advantages is that it supports containers, which is a promising emerging technology that offers tangible benefits over VMs. The migration performance of various real applications is evaluated by experiments under the presented framework. Insights drawn from the experimentation results are discussed.

cs.DC↗

arXiv2017

Online Placement of Multi-Component Applications in Edge Computing Environments

Mobile edge computing is a new cloud computing paradigm which makes use of small-sized edge-clouds to provide real-time services to users. These mobile edge-clouds (MECs) are located in close proximity to users, thus enabling users to seamlessly access applications running on MECs. Due to the co-existence of the core (centralized) cloud, users, and one or multiple layers of MECs, an important problem is to decide where (on which computational entity) to place different components of an application. This problem, known as the application or workload placement problem, is notoriously hard, and therefore, heuristic algorithms without performance guarantees are generally employed in common practice, which may unknowingly suffer from poor performance as compared to the optimal solution. In this paper, we address the application placement problem and focus on developing algorithms with provable performance bounds. We model the user application as an application graph and the physical computing system as a physical graph, with resource demands/availabilities annotated on these graphs. We first consider the placement of a linear application graph and propose an algorithm for finding its optimal solution. Using this result, we then generalize the formulation and obtain online approximation algorithms with polynomial-logarithmic (poly-log) competitive ratio for tree application graph placement. We jointly consider node and link assignment, and incorporate multiple types of computational resources at nodes.

cs.DC↗

arXiv2016

Dynamic Service Placement for Mobile Micro-Clouds with Predicted Future Costs

Mobile micro-clouds are promising for enabling performance-critical cloud applications. However, one challenge therein is the dynamics at the network edge. In this paper, we study how to place service instances to cope with these dynamics, where multiple users and service instances coexist in the system. Our goal is to find the optimal placement (configuration) of instances to minimize the average cost over time, leveraging the ability of predicting future cost parameters with known accuracy. We first propose an offline algorithm that solves for the optimal configuration in a specific look-ahead time-window. Then, we propose an online approximation algorithm with polynomial time-complexity to find the placement in real-time whenever an instance arrives. We analytically show that the online algorithm is $O(1)$-competitive for a broad family of cost functions. Afterwards, the impact of prediction errors is considered and a method for finding the optimal look-ahead window size is proposed, which minimizes an upper bound of the average actual cost. The effectiveness of the proposed approach is evaluated by simulations with both synthetic and real-world (San Francisco taxi) user-mobility traces. The theoretical methodology used in this paper can potentially be applied to a larger class of dynamic resource allocation problems.

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arXiv2015

Network Capability in Localizing Node Failures via End-to-end Path Measurements

We investigate the capability of localizing node failures in communication networks from binary states (normal/failed) of end-to-end paths. Given a set of nodes of interest, uniquely localizing failures within this set requires that different observable path states associate with different node failure events. However, this condition is difficult to test on large networks due to the need to enumerate all possible node failures. Our first contribution is a set of sufficient/necessary conditions for identifying a bounded number of failures within an arbitrary node set that can be tested in polynomial time. In addition to network topology and locations of monitors, our conditions also incorporate constraints imposed by the probing mechanism used. We consider three probing mechanisms that differ according to whether measurement paths are (i) arbitrarily controllable, (ii) controllable but cycle-free, or (iii) uncontrollable (determined by the default routing protocol). Our second contribution is to quantify the capability of failure localization through (1) the maximum number of failures (anywhere in the network) such that failures within a given node set can be uniquely localized, and (2) the largest node set within which failures can be uniquely localized under a given bound on the total number of failures. Both measures in (1-2) can be converted into functions of a per-node property, which can be computed efficiently based on the above sufficient/necessary conditions. We demonstrate how measures (1-2) proposed for quantifying failure localization capability can be used to evaluate the impact of various parameters, including topology, number of monitors, and probing mechanisms.

cs.NI↗

arXiv2015

Mobility-Induced Service Migration in Mobile Micro-Clouds

Mobile micro-cloud is an emerging technology in distributed computing, which is aimed at providing seamless computing/data access to the edge of the network when a centralized service may suffer from poor connectivity and long latency. Different from the traditional cloud, a mobile micro-cloud is smaller and deployed closer to users, typically attached to a cellular basestation or wireless network access point. Due to the relatively small coverage area of each basestation or access point, when a user moves across areas covered by different basestations or access points which are attached to different micro-clouds, issues of service performance and service migration become important. In this paper, we consider such migration issues. We model the general problem as a Markov decision process (MDP), and show that, in the special case where the mobile user follows a one-dimensional asymmetric random walk mobility model, the optimal policy for service migration is a threshold policy. We obtain the analytical solution for the cost resulting from arbitrary thresholds, and then propose an algorithm for finding the optimal thresholds. The proposed algorithm is more efficient than standard mechanisms for solving MDPs.

cs.DC↗

arXiv2012

A Methodology for Studying VANET Performance with Practical Vehicle Distribution in Urban Environment

In a Vehicular Ad-hoc Network (VANET), the amount of interference from neighboring nodes to a communication link is governed by the vehicle density dynamics in vicinity and transmission probabilities of terminals. It is obvious that vehicles are distributed non-homogeneously along a road segment due to traffic controls and speed limits at different portions of the road. The common assumption of homogeneous node distribution in the network in most of the previous work in mobile ad-hoc networks thus appears to be inappropriate in VANETs. In light of the inadequacy, we present in this paper an original methodology to study the performance of VANETs with practical vehicle distribution in urban environment. Specifically, we introduce the stochastic traffic model to characterize the general vehicular traffic flow as well as the randomness of individual vehicles, from which we can acquire the mean dynamics and the probability distribution of vehicular density. As illustrative examples, we demonstrate how the density knowledge from the stochastic traffic model can be utilized to derive the throughput and progress performance of three routing strategies in different channel access protocols. We confirm the accuracy of the analytical results through extensive simulations. Our results demonstrate the applicability of the proposed methodology on modeling protocol performance, and shed insight into the performance analysis of other transmission protocols and network configurations in vehicular networks. Furthermore, we illustrate that the optimal transmission probability for optimized network performance can be obtained as a function of the location space from our results. Such information can be computed by road-side nodes and then broadcasted to road users for optimized multi-hop packet transmission in the communication network.

cs.NI↗

arXiv2010

On the Universality of Sequential Slotted Amplify and Forward Strategy in Cooperative Communications

While cooperative communication has many benefits and is expected to play an important role in future wireless networks, many challenges are still unsolved. Previous research has developed different relaying strategies for cooperative multiple access channels (CMA), cooperative multiple relay channels (CMR) and cooperative broadcast channels (CBC). However, there lacks a unifying strategy that is universally optimal for these three classical channel models. Sequential slotted amplify and forward (SSAF) strategy was previously proposed to achieve the optimal diversity and multiplexing tradeoff (DMT) for CMR. In this paper, the use of SSAF strategy is extended to CBC and CMA, and its optimality for both of them is shown. For CBC, a CBC-SSAF strategy is proposed which can asymptotically achieve the DMT upper bound when the number of cooperative users is large. For CMA, a CMA-SSAF strategy is proposed which even can exactly achieve the DMT upper bound with any number of cooperative users. In this way, SSAF strategy is shown to be universally optimal for all these three classical channel models and has great potential to provide universal optimality for wireless cooperative networks.

cs.IT↗

arXiv2010

Wireless Network Coding with Imperfect Overhearing

Not only is network coding essential to achieve the capacity of a single-session multicast network, it can also help to improve the throughput of wireless networks with multiple unicast sessions when overheard information is available. Most previous research aimed at realizing such improvement by using perfectly overheard information, while in practice, especially for wireless networks, overheard information is often imperfect. To date, it is unclear whether network coding should still be used in such situations with imperfect overhearing. In this paper, a simple but ubiquitous wireless network model with two unicast sessions is used to investigate this problem. From the diversity and multiplexing tradeoff perspective, it is proved that even when overheard information is imperfect, network coding can still help to improve the overall system performance. This result implies that network coding should be used actively regardless of the reception quality of overheard information.

cs.IT↗