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Cloud computing plays a vital role in today's IT industry, as it offers tremendous computing and storage facilities for the tasks and outsourced data respectively. The major security concern during the computations is to protect customer's confidential data. The mechanism of this paper decomposes widely applicable linear programming (LP) computation outsourcing into public LP solvers running on a...
This paper considers the resource allocation problem defined over a hybrid data center and edge server network, where the allocations are subject to integer constraints, taking the granularity of network resources and service requests into account. We develop two efficient heuristic algorithms to solve this nonconvex program, both based the alternating direction method of multipliers (ADMM) and a...
In this paper, we introduce MVPN, a framework for building secure Virtual Private Networks (VPNs) with a novel Mobile IPv6 based Moving Target Defense strategy. Our approach aids in combating remote attacks against a VPN server. By eliminating the static address of the server, we make it difficult for an attacker to find the server. The server''s address is randomly changed at a certain interval creating...
Mobile cloud computing is increasingly being used in recent times to offload parts of an application to the cloud to reduce its finish time. However, quality of offloading decisions depend on network conditions and hence many offloading solutions assume that MAC layer retransmissions will tackle transient frame errors. This can lead to suboptimal solutions, as well as, degrade service level guarantee...
Wireless caching at users' devices in mobile social network is considered to be a promising solution to alleviate backhaul overload in future wireless networks. However, most of the current works propose caching schemes based on heuristic reasoning and intuition with poor performance or high complexity which are impractical due to individual devices' computing capacity restriction. In this paper,...
Resource abstraction aims at enabling flexible allocation of capacity to serve demands by aggregating physical resources taken out of distributed resource pools accessible via dedicated gateways. This paradigm sits at the heart of many networking models including resource virtualization and other cloud computing. In this paper, we show this generic problem can be modeled by combining and extending...
Mobile-edge computing (MEC) has recently emerged as a promising paradigm to liberate mobile devices from increasingly intensive computation workloads, as well as to improve the quality of computation experience. In this paper, we investigate the tradeoff between two critical but conflicting objectives in multi-user MEC systems, namely, the power consumption of mobile devices and the execution delay...
In cloud systems, efficient resource provisioning is needed to maximize the resource utilization while reducing the Service Level Objective (SLO) violation rate, which is important to cloud providers for high profit. Several methods have been proposed to provide efficient provisioning. However, the previous methods do not consider leveraging the complementary of jobs' requirements on different resource...
Nowadays, data centers deploy a large number of servers and network devices to provide various service functions (e.g. firewalls, deep packet inspection, content caches, WAN optimizers, etc.) and sufficient network connection. Most traffic in data centers is subject to treatment by multiple service functions (SFs) which form an ordered service function chain (SFC). In this paper, we study the energy-aware...
In this work, we study the problem of allocating two types of memory, which have different access speeds, to a set of routers in a single content-centric network. Total network delay is adopted as the performance metric. We first formulate the allocation problem and show that it is NP-hard. Then we prove that this problem is monotone submodular with a matroid constraint. Hence, we are able to derive...
Cloud computing and Network Function Virtualization (NFV) represent together a promising solution for wireless network operators to improve business agility and cope with the continuing growth in data traffic. Furthermore, the use of edge clouds in association with a centralized cloud, referred to as the edge-central cloud, notably improves user experience while ensuring scalability and load balancing...
Many real-world machine learning applications involveseveral learning tasks which are inter-related. For example, in healthcare domain, we need to learn a predictive model of a certain disease for many hospitals. The models for each hospital may be different because of the inherent differences in the distributions of the patient populations. However, the models are also closely related because of...
We describe a scheduler for multiple servers shared among different packet-flows, where each packet-flow may be served by only a subset of available (preferred) servers. The scheduler allocates tokens to flows in a round-by-round manner, where token allocation to flows at the beginning of each round is weighted max-min fair. We present a packet scheduling scheme where when a server becomes free, it...
This paper initiates a new study on online partitioning algorithms that are sequentially optimized for a query sequence. As queries arrive one at a time, given the option to reconfigure the partition after each query so that it can best serve the next query, the objective is to minimize the query read cost and data migration cost. This is an online problem without an optimal solution; online heuristics...
A Content Delivery Network (CDN) is a dynamic and complex service system. It causes a huge amount of traffic on the network infrastructure of Internet Service Providers (ISPs). Oftentimes, CDN providers and ISPs struggle to find an efficient and appropriate way to cooperate for mutual benefits. This challenge is key to push the quality of service (QoS) for the end-user. We model, simulate, and optimize...
In Infrastructure-as-a-Service clouds, users can reduce costs by scale-in or-down when running applications are under-utilized. Since these optimizations of instance deployment require at least one minimum instance even for running an under-utilized application, cost reduction is limited. For further optimization, multiple applications can be consolidated into one instance. However, applications have...
For achieving various network optimization and management goals in data centers, some VMs need to be migrated from the initial servers to the target ones. Live VM migration is an effective technique to achieve these goals. When multiple VMs need to be migrated at the same time, the migration order and migration bandwidth has a great impact on migration performance. For making an effective VM migration...
The convergence of high-performance computing and big data, which has become known as the field of extreme big data, is problematic in that file creation in storage systems such as distributed file systems is not optimized. That is, the large workload leads to the simultaneous creation of many files by many processes when creating checkpoints. The need to improve the file creation processes prompted...
Container technology has become popular in HPC applications because it offers easy customization and quick execution. However, container technology does not allow kernel-level optimization. It does not allow changing a kernel as well as loading/unloading a kernel module, thus it prevents the extraction of full performance on a target machine. In addition, container technology is designed for multi-tenancy...
The k-center problem is a fundamental problem we often face when considering complex service systems. Typical challenges include the placement of warehouses in logistics or positioning of servers for content delivery networks. We previously have proposed Dragoon as an effective algorithm to approach the k-center problem. This paper evaluates Dragoon with a focus on potential worst case behavior in...
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