Every switch collects the utilization percentages of the core and outgoing links connected to it as well as its own utilization percentage, then packetizes this information and sends it to the thermal predictor through the wireless channel. Once the thermal predictor receives this information, the predictor estimates the future temperature profile of the chip so as to trigger the combined dynamicthermalmanagementscheme that is proposed in this thesis. Due to the usage of WIs efficiently in the WiNoC, the overall hop count is reduced, and the switches and cores receive the thermal control packets quickly. The combined effect of the wireless transmission of control information along with the prediction based triggering of the thermalmanagementscheme ensures a quick response making sure there are no transient overshoots in temperature above the defined target temperature threshold. In the following two sub-sections let us look at the topology of the WiNoC and the physical layer of the wireless interconnects that are used to setup the simulation environment. This WiNoC discussed, forms the platform on which we evaluate the proposed combined DTM technique.
To meet the Quality of Service (QoS) required by cloud users in the context of fluctuating IT workloads, data center operators usually over-provision the computing resource according to the peak workload. As a result, the IT resource is extremely underutilized (20 − 30%  in typical data centers). Staggeringly, server energy con- sumption is out of proportion to its utilization, and energy consumed by an idle server is about 60% of a fully uti- lized counterpart . Controlling the sleep/active state of servers is proved to be an effective way to save IT energy. Meisner et al.  presented an energy conser- vation approach named PowerNap, which switches the operation state of servers between active and sleep modes to cater for the fluctuating workload. However, when the actual idle interval is less than the wake-up latency, the frequent switch between active and sleep modes may be negative for energy saving. To address this issue, Duan et al.  proposed a prediction scheme, which dynami- cally estimates the length of CPU idle interval and thereby intelligently picks out the most cost-efficient operation mode to effectively cut down idle energy.
respectively. A detailed comparison is depicted in Table VIII. It should be noted that the average temperature is the mean of four cores temperature running programs simultaneously from beginning to the end. Hence, compared to Linux, PDTM and TAS, our proposed method indeed leads to more peak temperature reduction with negligible performance overhead. In the Linux scheduler, one core starts program execution and terminates it due to high migration threshold assignment. Therefore, it does not use other cooler cores to decrease the hot core temperature. PDTM tries to mitigate problem using core temperature prediction; however, it cannot find a proper core when all cores temperatures are near to the temperature threshold (70 ◦ C). In such circumstances, the task migrates between different cores repeatedly. This phenomenon is known as Ping-Pong effect . TAS categorizes applications based on their thermal behavior to improve prediction accuracy. It defines an appropriate core as a core that reaches to migration threshold later. Our proposed technique improves TAS algorithm using an adjustable threshold scheme and an improved predictor. As shown before, adjustable threshold leads the scheduler to assign tasks to a core which reaches T ss as late as possible.
ThreshHot scheduler. In contrast to MinTemp + , our Thresh- Hot algorithm first estimates the temperatures for all jobs in the next time window and then selects the hottest job that will not exceed the threshold (according to the estimates). Hence, at the beginning of an epoch in Figure 4(d), the hot job is selected to run until the temperature is too close to the threshold. At this point, the scheduler decides to discontinue the hot job and swap in the warm job because it predicts that the warm job will not create a thermal violation in the next interval. The warm job now will run for several intervals until the temperature is low enough for running another hot job slice. As we can see from the figure, at the beginning of each epoch, the scheduler toggles between the hot and the warm job, allocating longer duration for the latter (as opposed to switching between the hot and cool job in MinTemp + ). Later in the epoch, warm job’s quantum is used up, so the scheduler toggles between the hot and the cool job with longer duration allocated to the latter as well. Such a scheme effectively keeps the temperature right below the thresh- old achieving the least amount of frequency scaling. For the two epochs shown in the figures, the ThreshHot scheduling shows that it is possible to greatly reduce or even avoid frequency scal- ing if the jobs are arranged in a good order.
67 MODULAR, LIGHTWEIGHT, SYNTHETIC, WOODLAND, DESERT AND SNOW” are two of the most relevant military specifications and standards. MIL-PRF-53134 appears to still be active, but MIL-C-53004B has been listed as inactive for new systems and thus is somewhat less useful . Usefully most military standards, including these two are available for free to the public. Outside of the military standards and specifications, researchers may want to consider reviewing a ULCANS operational and maintenance manuals for extra details. The military standards usefully clarify the test methods that should be used for various properties and the performance requirements for each. For instance, MIL-PRF-53134 sets breaking strength requirements for the netting system’s materials prior to exposure with woven materials as 55 lbs in the warp and 80 lbs in the fill and for the garnish 40 lbs in the warp and 40 lbs in the fill . It also gives some guidance for how to assess the netting system’s thermal signature. According to the standard, testing should be carried out outdoors in an open area with full sun exposure with the ULCANS set up according to how it is intended to be used in real world application . The ULCANS should be observed by imagers after the system has been exposed to solar radiation levels greater than 800 W/m 2 for at least one hour . Wind speeds should be less than 2 m/s during testing and the imager should be at ground level while it observes the netting systems in the 3 to 5 µm and 8 to 12 µm wavebands . In order to calibrate the thermal imager for this test, a black body material with an emissivity of 0.98 or more that is shielded from
Now that Power LEDs are capable of unprecedented levels of white LED brightness and luminous efficacy, they are being used in many products that are part of our daily lives. Although today the initial cost of Power LEDs is higher, many applications have demonstrated LED lighting as the most cost or energy efficient solution for future installations. Equipment manufacturers worldwide are making devices with Power LEDs for both the commercial and consumer segments. With smaller footprints, our products lead the way in reducing the buildup of heat and maximize the LED’s potential benefits. Bergquist provides critical thermalmanagement support for a myriad of Power LED applications that include: medical, signage, signal, transportation, aircraft, automotive, security, portable, theatrical, commercial, residential and street lighting.
Several works have been presented in the literature to address the above-mentioned issues. The existing circuit techniques try to improve some of the design characteristics at the cost of degrading others. These circuits usually change the circuit topology of the evaluation network or the keeper scheme. Recently, some techniques have been proposed in the literature in which the evaluation network and the keeper circuit are restructured simultaneously to improve most of the characteristics [7-10].
1) There exists the forgery attack in PMD. PMD uses an ordinary signature scheme such as RSA to sign DI root. When PMD deals with a user query, server returns the query results and the authentication objects including the data owner's signature to the user, thus exposes the data owner's signature. The ordinary signature is self- proven and can be passed. Anyone can verify the correctness of the signature and data as long as access to the signature. If an attacker intercepts the data and verification information that are uploaded to the server by data owner, he can impersonate the server to provide services for users or distribute the data owner's data and signatures. If a user already obtains the data and the authentication objects including the data owner's signature, he can impersonate the server to provide services for users or distribute the data owner's data and signatures. It is not permitted in practical applications such as payment services through the server.
Reference  proposes a new methodology based on risk management and quantitative analysis for the time response curves, and coordination between UFLS and UVLS is studied. A UFLS scheme, based on non-recur- ve Newton algorithm to estimate the frequency and the frequency change ratio, is put forward . Concerning the frequency characteristic difference of different load nodes, reference  puts forward a load shedding scheme base on comprehensive weights. References [4, 5] pro- pose a low-order model to calculate the response of the system with disturbance. A load shedding method ensur- ing the stability of both frequency and voltage is studied in . In a word, references mentioned above are all based on the low-order frequency response model to calculate the deficit power. Nevertheless, the model ig- nores the effect of voltage on the deficit power, resulting in some error in the deficit power calculation.
The ultimate purpose of this study is to find out the optimal packet length for the real time channel conditions. The basic idea is: if the packet length is too small, much transmission is spent on handling packet headers which result in low effective data throughput. Therefore, we need some optimal packet length exists to achieve maximal throughput on the other hand, if the packet length is too large, due to packet error rate, packet retransmission rate will be high. This packet optimization scheme applicable in sensor networks only. This sensor network must have the following features.
ABSTRACT Users benefit from cloud computing, and can achieve an efficient and economical approach to sharing data among cloud group members with low-maintenance characters and low management costs. In the meantime, we must provide security guarantees to share data files because they are outsourced. Unfortunately, because of the frequent change of membership, sharing data while maintaining privacy is still a difficult issue, especially for an unreliable cloud due to the attack of collusion. Moreover, for existing schemes, key distribution security depends on the secure communication channel, however, assuming that this channel is a strong and difficult enforcement practice. In this paper, we propose a secure data sharing plan for dynamic members. First, we suggest a secure way to distribute keys without any secure connection channels, and users can get their own keys securely from the group manager. Second, our system can achieve strict access control, a user in the group who can use the source in the cloud and cancel
limit the borders of a ROI. There are three approaches in which regions of interest can be determined. The first one is based on the analysis of 2D thermal images, which is very practical in cases when temperature of the body ex- hibits rapid localised changes. These inflamed areas are easily detected using common image processing tech- niques, such as image segmentation and edge detection. Thermal image analysis can be performed completely au- tomatically, or by manual selection of a specific area for inflammation localisation. The coordinates of an inflam- mation’s border can be determined in 3D space using defined texture coordinates of standardised human body 3D thermal model. The second approach for ROI detec- tion is based on the analysis of human body 3D thermal model, both scanned and standardised. Manually select- ed ROI borders of the scanned human body 3D thermal model can be converted to the standardised 3D thermal model space by using known texture mapping parameters calculated in standardisation procedure. The third ap- proach is given as the combination of the former two: 2D thermal image features and spatial characteristics of 3D model of the subject’s body. Once identified on the tem- plate model, ROI location can be compared with any other standardised 3D thermal model that has been ac- quired, thus providing the option of monitoring the tem- perature of a specific region over time, or comparison of that region with the scans from several different human subjects.
Abstract: Load balancing is a very important issue in parallel and distributed systems to ensure fast processing and optimum utilization of computing resources. Dynamic load balancing scheme is use for minimizing the execution time of single application running in parallel on multicomputer system. Dynamic load balancing is good for efficient use of highly parallel system. In a large distributed computing environment, multiple processes or task can be submitted at any node and the random arrival of tasks in such an environment can cause some nodes to be high loaded while others are idle or low loaded. For some many applications, computation load varies over time. Such applications require dynamic load balancing to increase performance. Some of the load balancing scheme or systems is already existed like centralize load balancing, hierarchical load balancing but some of the limitations in this existing system. The Centralized load balancing schemes, which perform the load balancing decisions at a central location, are not scalable that’s why we concentrate on dynamic load balancing. This paper present introduction of our system and there modules like task creation, task scheduling, task migration and resource allocation. This paper include the result of our proposed system time after load balancing and result of task migration if any of performer is busy.
Air to air heat exchangers are the ideal choice of thermalmanagement when the external temperature is lower than the internal requested temperature and a maintenance free solution is mandatory. Protection degree of IP54/IP55 is granted and the internal patented aluminium core provides high efficiency and safety.
In this study, the WRF model was utilized as a dynamic downscaling tool to analyse the influence of horizontal resolution and domain size on precipitation forecasting over Xijiang basin. Several typical rainstorms were simulated under different downscaling schemes. An optimized dynamic downscaling scheme has been established. The conclusions are drawn as follows:
distribution and data sharing for dynamic group. We provide a secure way for key distribution without any secure communication channels. The users can securely obtain their private keys from group manager without any Certificate Authorities due to the verification for the public key of the user. Our scheme can achieve fine-grained access control, with the help of the group user list, any user in the group can use the source in the cloud and revoked users cannot access the cloud again after they are revoked. We propose a secure data sharing scheme which can be protected from collusion attack. The revoked users can not be able to get the original data files once they are revoked even if they conspire with the untrusted cloud. Our scheme can achieve secure user revocation with the help of polynomial function. Our scheme is able to support dynamic groups efficiently, when a new user joins in the group or a user is revoked from the group, the private keys of the other users do not need to be recomputed and updated. We provide security analysis to prove the security of our scheme.
The increase in energy demand has led to expansion of renewable energy sources and their integration into a more diverse energy mix. Consequently the operation of thermal power plants, which are spearheaded by the gas turbine technology, has been affected. Gas turbines are now required to operate more flexibly in grid supporting modes that include part load and transient operations. Therefore, condition based maintenance should encapsulate this recent shift in the gas turbine’s role by taking into account dynamic operating condi- tions for diagnostic and prognostic purposes. In this paper, a novel scheme for performance-based prognostics of industrial gas turbines operating under dynamic conditions is proposed and developed. The concept of performance adaptation is introduced and implemented through a dynamic engine model that is developed in Matlab/Simulink environment for diagnosing and prognosing the health of gas turbine components. Our proposed scheme is tested under variable ambient conditions corresponding to dynamic operational modes of the gas turbine for estimating and predicting multiple component degradations. The diagnosis task developed is based on an adaptive method and is performed in a sliding window-based manner. A regression-based method is then implemented to locally represent the diagnostic information for subsequently forecasting the performance behavior of the engine. The accuracy of the proposed prognosis scheme is evaluated through the Probability Density Function (PDF) and the Remaining Useful Life (RUL) metrics. The results demonstrate a promising prospect of our proposed methodology for detecting and predicting accurately and efficiently the performance of gas turbine components as they degrade over time.
to three load levels, i.e. underloaded, balanced or overloaded, by comparing their load with the average load of APs. Then, each AP performs admission control based on its load level. If an STA is denied by an AP, the STA is then re-directed to a neighbor AP which is underloaded. Thus, STAs can associate with the underloaded AP such that the overall utilization of APs in a WLAN hotspot is improved. Bejerano et al.  further consider the fairness between STAs which are contending the bandwidths of APs in a hotspot. They apply the max-min fairness scheme to manage the bandwidth assignment of APs to STAs in a hotspot. Unfortunately, they assume STAs are requesting best effort services and contending WLAN channels with peer STAs. They do not consider the QoS requests. To allocate WLAN resources for QoS sessions such as VoWLAN service, Balachandran et al.  present a network-assisted mechanism. In this scheme, a cen- tralized server in the backbone network collects the load information of APs and an STA sends a request to the server before establishing a QoS connection. The server performs the admission control and finds a suitable AP for the STA. If more than one AP is found, the AP with the minimal load is recommended. This scheme only statically assigns STAs to APs while the STAs initially request QoS services, but does not consider the dynami- cal rearrangement of AP loads to optimize the overall utilization.
The use of global load information to move and split the grids eliminates the variabilityin time to reach the equal balance and avoids chances of thrashing . In other words, the situation that multiple overloaded processors send their workload to an underloaded processor and make it overloaded will not occur byusing the proposed DLB. Note that both the moving-grid phase and splitting-grid phase execute in parallel. For example, suppose there are eight processors as shown in Fig. 10. If the MaxProc and MinProc are processors 0 and 5, respectively, all the processors know which grid will be moved/split from processor 0 to processor 5 by the guidance of the global information. Then processor 0 moves/splits its grid (i.e. the ‘‘real’’ grid) to processor 5. In parallel, other processors ﬁrst update their view of load distribution of this grid movement from processor 0 to processor 5, then continue load-balancing process. If the new MaxProc and MinProc are processor 1 and 2 respectively, then processor 1 will move/split its grid (i.e. ‘‘real’’ grid) to processor 2, and this process will be overlapped with the movement from processor 0 to processor 5. The remaining processors (3, 4, 6 and 7) continue with ﬁrst updating their view of load distribution of the grid movement from processor 1 to processor 2 followed bycalculating the next MaxProc and MinProc. Because the new MaxProc and MinProc are processor 0 and 3, respectively, so processor 3 has to wait for processor 0 which is still in the process of transferring its workload to processor 5. In order to minimize the overhead of the scheme, nonblocking communication is explored in this scheme. In the mode of nonblocking communication, a nonblocking post-send initiates a send operation and returns before the message is copied out of the send buffer. A separate complete-send call is needed to complete the communication. The nonblocking receive is proceeded similarly. In this manner, the transfer of data mayproceed concurrentlywith computations done at both the sender and the receiver sides. In the splitting-grid phase, nonblocking calls are explored and being overlapped with several computation functions.