With the popularization of software defined networks, switch migration as an important network management strategy has attracted increasing attention. Most existing switch migration strategies only consider local conditions and simple load thresholds, without fully considering the overall optimization and dynamics of the network. Therefore, this article proposes a switch migration algorithm based on global optimization. This algorithm adds a load prediction module to the migration model, determines the migration controller, and uses an improved whale optimization algorithm to determine the target controller and its surrounding controller set. Based on the load status of the controller and the traffic priority of the switch to be migrated, the optimal migration switch set is determined. The experimental results show that compared to existing schemes, the algorithm proposed in this paper improves the average flow processing efficiency by 15% to 40%, reduces switch migration times, and enhances the security of the controller.

The concepts of programmable switches and software-defined networking (SDN) give developers flexible and deep control over the behavior of switches. We expect these concepts to dramatically improve the functionality of switches. In this paper, we focus on the concept of Deeply Programmable Networks (DPN), where data planes are programmable, and application switches based on DPN. We then propose a method to improve the performance of a key-value store (KVS) through an application switch. First, we explain the DPN and application switches. The DPN is a network that makes not only control planes but also data planes programmable. An application switch is a switch that implements some functions of network applications, such as database management system (DBMS). Second, we propose a method to improve the performance of Cassandra, one of the most popular key-value based DBMS, by implementing a caching function in a switch in a dedicated network such as a data center. The proposed method is expected to be effective even though it is a simple and traditional way because it is in the data path and the center of the network application. Third, we implement a switch with the caching function, which monitors the accessed data described in packets (Ethernet frames) and dynamically replaces the cached data in the switch, and then show that the proposed caching switch can significantly improve the KVS transaction performance with this implementation. In the case of our evaluation, our method improved the KVS transaction throughput by up to 47%.

This paper proposes a migration model for distributed server allocation. In distributed server allocation, each user is assigned to a server to minimize the communication delay. In the conventional model, a user cannot migrate to another server to avoid instability. We develop a model where each user can migrate to another server while receiving services. We formulate the proposed model as an integer linear programming problem. We prove that the considered problem is NP-complete. We introduce a heuristic algorithm. Numerical result shows that the proposed model reduces the average communication delay by 59% compared to the conventional model at most.

Due to the rapid development of different processors, e.g., x86 and Sunway, software porting between different platforms is becoming more frequent. However, the migrated software's execution efficiency on the target platform is different from that of the source platform, and most of the previous studies have investigated the improvement of the efficiency from the hardware perspective. To the best of our knowledge, this is the first paper to exclusively focus on studying what software factors can result in performance change after software migration. To perform our study, we used SonarQube to detect and measure five software factors, namely Duplicated Lines (DL), Code Smells Density (CSD), Big Functions (BF), Cyclomatic Complexity (CC), and Complex Functions (CF), from 13 selected projects of SPEC CPU2006 benchmark suite. Then, we measured the change of software performance by calculating the acceleration ratio of execution time before (x86) and after (Sunway) software migration. Finally, we performed a multiple linear regression model to analyze the relationship between the software performance change and the software factors. The results indicate that the performance change of software migration from the x86 platform to the Sunway platform is mainly affected by three software factors, i.e., Code Smell Density (CSD), Cyclomatic Complexity (CC), and Complex Functions (CF). The findings can benefit both researchers and practitioners.

Edge computing offers computing capability with ultra-low response times by leveraging servers close to end-user devices. Due to the mobility of end-user devices, the latency between the servers and the end-user devices can become long and the response time might become unacceptable for an application service. Service (container) migration that follows the handover of end-user devices retains the response time. Service migration following the mass movement of people in the same geographic area and at the same time due to an event (e.g., commuting) generates heavy bandwidth usage in the mobile backhaul network. Heavy usage by service migration reduces available bandwidth for ordinary application traffic in the network. Shaping the migration traffic limits the bandwidth usage while delaying service migration and increasing the response time of the container for the moving end-user device. Furthermore, targets of migration decisions increase (i.e., the system load) because delaying a migration process accumulates containers waiting for migration. In this paper, we propose a migration scheduling method to control bandwidth usage for migration in a network and ensure timely processing of service migration. Simulations that compare the proposal with state-of-the-art methods show that the proposal always suppresses the bandwidth usage under the predetermined threshold. The method reduced the number of containers exceeding the acceptable response time up to 40% of the compared state-of-the-art methods. Furthermore, the proposed method minimized the targets of migration decisions.

Here, we present a novel spectroscopic imaging method based on the boundary-extraction scheme for wide-beam terahertz (THz) three-dimensional imaging. Optical-lens-focusing systems for THz subsurface imaging generally require the depth of the object from the surface to be input beforehand to achieve the desired azimuth resolution. This limitation can be alleviated by incorporating a wide-beam THz transmitter into the synthetic aperture to automatically change the focusing depth in the post-signal processing. The range point migration (RPM) method has been demonstrated to have significant advantages in terms of imaging accuracy over the synthetic-aperture method. Moreover, in the RPM scheme, spectroscopic information can be easily associated with each scattering center. Thus, we propose an RPM-based terahertz spectroscopic imaging method. The finite-difference time-domain-based numerical analysis shows that the proposed algorithm provides accurate target boundary imaging associated with each frequency-dependent characteristic.

In this paper, we propose a scalable and seamless connection migration scheme for moving target defense in legacy networks. The main idea is that a host is allowed to receive incoming packets with a destination address that is either its current IP address or its previous IP address for a period of time because the host does not physically move into another network. Experimental results show that our scheme outperforms the existing connection migration mechanism regardless of the number of active connections in the host.

Large-scale virtualized data centers are increasingly becoming the norm in our data-intensive society. One pressing challenge is to reduce the energy consumption of servers while maintaining a high level of service agreement fulfillment. Due to the convenience of virtualization, virtual machine migration is an effective way to optimize the trade-off between energy and performance. However, there are obvious drawbacks in the current static threshold strategy for migration. This paper proposes a new decision strategy based on decision-theoretic rough sets. In the new strategy, the status of a server is determined by the Bayesian rough set model. The space is divided into positive, negative and boundary regions. According to this information, a migration decision with minimum risk will be made. This three-way decision framework in our strategy can reduce over-migration and delayed migration. The experiments in this paper show that this new strategy outperforms the benchmark examined. It is an efficient and flexible approach to the energy and performance trade-off in the cloud.

High energy cost is a big challenge faced by the current data centers, wherein computing energy and cooling energy are main contributors to such cost. Consolidating workload onto fewer servers decreases the computing energy. However, it may result in thermal hotspots which typically consume greater cooling energy. Thus the tradeoff between computing energy decreasing and cooling energy decreasing is necessary for energy saving. In this paper, we propose a minimized-total-energy virtual machine (VM for short) migration model called C2vmMap based on efficient tradeoff between computing and cooling energies, with respect to two relationships: one for between the resource utilization and computing power and the other for among the resource utilization, the inlet and outlet temperatures of servers, and the cooling power. Regarding online resolution of the above model for better scalability, we propose a VM migration algorithm called C2vmMap_heur to decrease the total energy of a data center at run-time. We evaluate C2vmMap_heur under various workload scenarios. The real server experimental results show that C2vmMap_heur reduces up to 40.43% energy compared with the non-migration load balance algorithm. This algorithm saves up to 3x energy compared with the existing VM migration algorithm.

By focusing on the recent swing to the centralized approach by the software defined network (SDN), this paper presents a novel network architecture for refactoring the current distributed Internet protocol (IP) by not only utilizing the SDN itself but also implementing its cooperation with the optical transport layer. The first IP refactoring is for flexible network topology reconfiguration: the global routing and explicit routing functions are transferred from the distributed routers to the centralized SDN. The second IP refactoring is for cost-efficient maintenance migration: we introduce a resource portable IP router that can behave as a shared backup router by cooperating with the optical transport path switching. Extensive evaluations show that our architecture makes the current IP network easier to configure and more scalable. We also validate the feasibility of our proposal.

Virtual Machine Placement (VMP) plays an important role in ensuring efficient resource provisioning of physical machines (PMs) and energy efficiency in Infrastructure as a Service (IaaS) data centers. Efficient server consolidation assisted by virtual machine (VM) migration can promote the utilization level of the servers and switch the idle PMs to sleep mode to save energy. The trade-off between energy and performance is difficult, because consolidation may cause performance degradation, even service level agreement (SLA) violations. A novel residual available capacity (RAC) resource model is proposed to resolve the VM selection and allocation problem from the cloud service provider (CSP) perspective. Furthermore, a novel heuristic VM selection policy for server consolidation, named Minimized Square Root available Resource (MISR) is proposed. Meanwhile, an efficient VM allocation policy, named Balanced Selection (BS) based on RAC is proposed. The effectiveness validation of the BS-MISR combination is conducted on CloudSim with real workloads from the CoMon project. Evaluation results of experiments show that the proposed combinationBS-MISR can significantly reduce the energy consumption, with an average of 36.35% compared to the Local Regression and Minimum Migration Time (LR-MMT) combination policy. Moreover, the BS-MISR ensures a reasonable level of SLAs compared to the benchmarks.

Ultra-wideband millimeter wave radars significantly enhance the capabilities of three-dimensional (3D) imaging sensors, making them suitable for short-range surveillance and security purposes. For such applications, developed the range point migration (RPM) method, which achieves highly accurate surface extraction by using a range-point focusing scheme. However, this method is inaccurate and incurs great computation cost for complicated-shape targets with many reflection points, such as the human body. As an essential solution to this problem, we introduce herein a range-point clustering algorithm that exploits, the RPM feature. Results from numerical simulations assuming 140-GHz millimeter wavelength radar verify that the proposed method achieves remarkably accurate 3D imaging without sacrificing computational efficiency.

In this letter, we propose a garbage collection technique for non-volatile memory systems, called Migration Cost Sensitive Garbage Collection (MCSGC). Considering the migration overhead from selecting victim blocks, MCSGC increases the lifetime of memory systems and improves response time in garbage collection. Additionally, the proposed algorithm also improves the efficiency of garbage collection by separating cold data from hot data in valid pages. In the experimental evaluation, we show that MCSGC yields up to a 82% improvement in lifetime prolongation, compared with existing garbage collection, and it also reduces erase and migration operations by up to 30% and 29%, respectively.

Live migration plays an important role on improving efficiency of cloud data centers by enabling dynamically replacing virtual machines (VMs) without disrupting services running on them. Although many studies have proposed acceleration mechanisms of live migration, IO-intensive VMs still suffer from long total migration time due to a large amount of page cache. Existing studies for this problem either force the guest OS to delete the page cache before a migration, or they do not consider dynamic characteristics of cloud data centers. We propose a parallel and adaptive transfer of page cache for migrating IO-intensive VMs which (1) does not delete the page cache and is still fast by utilizing the storage area network of a data center, and (2) achieves the shortest total migration time without tuning hand-crafted parameters. Experiments showed that our method reduces total migration time of IO-intensive VMs up to 33.9%.

Ultra-wideband radar exhibits high range resolution, and excellent capability for penetrating dielectric media, especially when using lower frequency microwaves. Thus, it has a great potential for innovative non-destructive testing of aging roads or bridges or for non-invasive medical imaging applications. In this context, we have already proposed an accurate dielectric constant estimation method for a homogeneous dielectric medium, based on a geometrical optics (GO) approximation, where the dielectric boundary points and their normal vectors are directly reproduced using the range point migration (RPM) method. In addition, to compensate for the estimation error incurred by the GO approximation, a waveform compensation scheme employing the finite-difference time domain (FDTD) method was incorporated. This paper shows the experimental validation of this method, where a new approach for suppressing the creeping wave along the dielectric boundary is also introduced. The results from real observation data validate the effectiveness of the proposed method in terms of highly accurate dielectric constant estimation and embedded object boundary reconstruction.

Postcopy live migration is a promising alternative of virtual machine (VM) migration, which transfers memory pages after switching the execution host of a VM. It allows a shorter and more deterministic migration time than precopy migration. There is, however, a possibility that postcopy migration would degrade VM performance just after switching the execution host. In this paper, we propose a performance improvement technique of postcopy migration, extending the para-virtualized page fault mechanism of a virtual machine monitor. When the guest operating system accesses a not-yet-transferred memory page, our proposed mechanism allows the guest kernel to defer the execution of the current process until the page data is transferred. In parallel with the page transfer, the guest kernel can yield VCPU to other active processes. We implemented the proposed technique in our postcopy migration mechanism for Qemu/KVM. Through experiments, we confirmed that our technique successfully alleviated performance degradation of postcopy migration for web server and database benchmarks.

Microwave ultra-wideband (UWB) radar systems are advantageous for their high-range resolution and ability to penetrate dielectric objects. Internal imaging of dielectric objects by UWB radar is a promising nondestructive method of testing aging roads and bridges and a noninvasive technique for human body examination. For these applications, we have already developed an accurate internal imaging approach based on the range points migration (RPM) method, combined with a method that efficiently estimates the dielectric constant. Although this approach accurately extracts the internal boundary, it is applicable only to highly conductive targets immersed in homogeneous dielectric media. It is not suitable for multi-layered dielectric structures such as human tissues or concrete objects. To remedy this limitation, we here propose a novel dielectric constant and boundary extraction method for double-layered materials. This new approach, which simply extends the Envelope method to boundary extraction of the inner layer, is evaluated in finite difference time domain (FDTD)-based simulations and laboratory experiments, assuming a double-layered concrete cylinder. These tests demonstrate that our proposed method accurately and simultaneously estimates the dielectric constants of both media and the layer boundaries.

With the growth of cloud-based services, cloud data centers are experiencing large growth. A key component in a cloud data center is the network technology deployed. In particular, Ethernet technology, commonly deployed in cloud data centers, is already envisioned for 10 Tbps Ethernet. In this paper, we study and analyze the makespan, workload execution times, and virtual machine migrations as the network speed increases. In particular, we consider homogeneous and heterogeneous data centers, virtual machine scheduling algorithms, and workload scheduling algorithms. Results obtained from our study indicate that the increase in a network's speed reduces makespan and workloads execution times, while aiding in the increase of the number of virtual machine migrations. We further observed that the number of migrations' behaviors in relation to the speed of the networks also depends on the employed virtual machines scheduling algorithm.

Radar systems using ultra-wideband (UWB) signals have definitive advantages in high range resolution. These are suitable for accurate 3-dimensional (3-D) sensing by rescue robots operating in disaster zone settings, where optical sensing is not applicable because of thick smog or high-density gas. For such applications, where no a priori information of target shape and position is given, an accurate method for 3-D imaging and motion estimation is strongly required for effective target recognition. In addressing this issue, we have already proposed a non-parametric 2-dimensional (2-D) imaging method for a target with arbitrary target shape and motion including rotation and translation being tracked using a multi-static radar system. This is based on matching target boundary points obtained using the range points migration (RPM) method extended to the multi-static radar system. Whereas this method accomplishes accurate imaging and motion estimation for single targets, accuracy is degraded severely for multiple targets, due to interference effects. For a solution of this difficulty, this paper proposes a method based on a novel matching scheme using not only target points but also normal vectors on the target boundary estimated by the Envelope method; interference effects are effectively suppressed when incorporating the RPM approach. Results from numerical simulations for both 2-D and 3-D models show that the proposed method simultaneously achieves accurate target imaging and motion tracking, even for multiple moving targets.

Ultra-wide band (UWB) radar has a great advantage for range resolution, and is suitable for 3-dimensional (3-D) imaging sensor, such as for rescue robots or surveillance systems, where an accurate 3-dimensional measurement, impervious to optical environments, is indispensable. However, in indoor sensing situations, an available aperture size is severely limited by obstacles such as collapsed furniture or rubles. Thus, an estimated region of target image often becomes too small to identify whether it is a human body or other object. To address this issue, we previously proposed the image expansion method based on the ellipse extrapolation, where the fitting space is converted from real space to data space defined by range points to enhance the extrapolation accuracy. Although this method achieves an accurate image expansion for some cases, by exploiting the feature of the efficient imaging method as range points migration (RPM), there are still many cases, where it cannot maintain sufficient extrapolation accuracy because it only employs the single scattered component for imaging. For more accurate extrapolation, this paper extends the above image expansion method by exploiting double-scattered signals between the target and the wall in an indoor environment. The results from numerical simulation validate that the proposed method significantly expands the extrapolated region for multiple elliptical objects, compared with that obtained using only single scattered signal.