Dynamic Power Management and Monitoring ...

International Journal of Computer Trends and Technology (IJCTT) – Volume 38 Number 2- August 2016

Dynamic Power Management and Monitoring Scheme for DRN-HA Cluster Bishnu Prasad Gautam#1, Narayan Sharma*2, Krishna Prasad Bhattarai#3 #

Assoc. Professor, Integrated Media, Wakkanai Hokusei Gakuen University, Wakabadai 1-2290-28, Wakkanai, Hokkaido, Japan 1 [email protected] 2 [email protected] 3 [email protected]

Abstract Disaster Ready Network (DRN) can offer stable services for users. Nonetheless, stable services cannot be provided without reliable scheme of power management. Disaster readiness is not possible when there is no reliable power management. Power management is becoming a great deal of attention for the researcher around the world in order to save energy and reduce the cost. Furthermore, DRN networks with high availability is difficult to arrange. The DPMM (Dynamic Power Management and Monitoring) scheme that we offer in this paper is a key power management system for automated management of computing utilities and power supply for the DRNs. This paper describes how a DRN networks can achieve proactive power management that enhances service continuity or stability and adaptive power utilization that further drives down power and cooling costs. We will highlight the power management technique of DVS (Dynamic Voltage Scaling) in circuit level considering the whole system. Keywords — DRN, HA Cluster, Dynamic Power Management. I.

INTRODUCTION

HA cluster[1]–[4] is a cluster consisting of several computing resources connected and working together which is designed in Gautam-Asami lab of Wakkanai University by primary authors of this paper. This cluster is aimed to provide stable services as a tool of disaster ready networks[1], [3]. In this research we are designing a portable power supply system with multipurpose applications. This system will be able to supply the on demand power to the required components and PC devices of HA cluster without interruption in power by using hardware based power management technique. Using appropriate power management techniques, the lifetime for batteryoperated systems could be extended and the heat dissipation could be decreased, lowering the requirement for expensive packaging and cooling technology[5]. The main feature of this system is that this system can interact with the users with its smart features and functionalities. A smart power supply

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system which is able to supply the on demand power to the external devices connected with Raspberry Pi. We further extended the features of external peripherals so that the power management system further supports other USB based devices, mobile phones, router, switch laptops and several other accessories. Proper power management technique is important not only to provide correct voltage or current rating to the system but also to reduce energy consumption. In order to reduce dynamic power and static power consumption, there are two popular methods available in the literature, i.e., Dynamic Voltage Scaling (DVS) and Dynamic Power Management (DPM), respectively. Generally, DVS is applied to scale the voltage requirement of CPU and other computing components. It reduces the power consumption of a particular components by adjusting the power requirement of that particular device. Nonetheless, in this research we apply this method for the entire system rather than going into particular component. On the basis of this method, we designed a smart power management system in order to supply uninterrupted power to those devices connected to it. We are using Raspberry Pi and Arduino Nano in order to control the overall power based control system. Arduino Nano is applied in order to control the power output ports so that one output USB port can support upto 4-6 RPi with loads. Loads in this case means the load from external devices attached by USB such as Wi-Fi dongles. In order to achieve this function Arduino performs the switching operation so that when load increases in ports Arduino will contributes by switching ON the voltage regulator devices. We are using LM series power adjustable linear voltage regulator IC in this research. II. PROBLEM FORMULATION AND REQUIREMENT ANALYSIS

Primary author of this research has been involved in designing and development of stable networks for unstable environment[1], [6]–[8] since few years back. Furthermore, he has also proposed and designed a disaster ready network during his Ph.D. study. In this research, we have noted few challenging tasks.

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Figure 1: HA Cluster Designed in Gautam-Asami Laboratory

This research suggests that disaster readiness should be considered in each layer of TCP/IP. However, the main challenging task seems to be how to provide a stable power supply in those kinds of unstable environment. Secondly, the power supply system for HA cluster (A disaster ready cluster that the author has developed) has faced under voltage problems and irregularities. Under voltage problems have been emerged while the cluster nodes are equipped with other power consuming modules. Figure 2 shows the current structure of HA cluster developed in our lab. This cluster is provided with external power supply in which each node is provided by separate power source. In this structure, power management is becoming a challenging tasks in terms of voltage scaling and efficiency. Particularly, when we plugged Wi-Fi dongles in the USB port of the cluster node, it comes up with under voltage problem. The problem with this system was that while we plugged more than one Wi-Fi dongles in the raspberry PI, it draws over power, pulling the voltage low and generate heats that ultimately halt the system and may physically damage the computing resources. In fact, HA cluster is working by utilizing the separate power supplies for each system or PCs connected in HA cluster. The number of Raspberry pi used in HA cluster needs separate power supply for running which is getting tidies in present time and unmanaged. This research work will be able to integrate all those power supply system into one for uninterrupted power supply. This system will also supports for other external devices. Our research work will be able to answer the following major problems.

especially for network design that considers disaster readiness. Research works are also focused in this area in order to assure the fault tolerant capacity of the networks. In case of computer networks, power management is the most critical issue because without stable power supply, network services are not possible. Thus, power management has been a prominent area of research not only for electrical engineers but also for electronics and communication engineers too. In most of the cases, power supply is designed by considering the peak load of the system and they provide maximum threshold at all times. However, this method consumes a lot of power and thus not a cost effective. In contrast if you provide the minimum threshold, power supply would not be sufficient to fully utilize the computing resources. In order to sort out this problem, several research projects are underway. Most of the power management techniques are used for the power management of CPU. For example, AVS, DPS and DVFS are used for active power management. In[9], Ghislain et al. use CPU frequency scaling to reduce the overall energy consumption of a HPC system. Their approach present a general purpose methodology for optimizing energy performance of HPC systems considering processor, disk and network[9]. Authors in [10] presented a theoretical and experimental framework to optimize power and performance at runtime for e-business data centres. They proposed to scale the memory size in order to minimize the power consumption. In [11] authors have proposed an autonomic power management scheme both for data and internet servers. While having in common the concept of power management during uptime, our work differs from those above in three major ways. First our power demand approach does not rely on a specific hardware or software systems. Second, unlike previous research efforts, those mostly focus to reduce the power consumption of CPU and memory our model does not only focus on power saving but utilize on demand power switching capabilities. Thirdly AVS applied in most of their works are solely dependent of CPU and memory operation voltage. However, in our work, voltage scaling is not dependent only with CPU or memory processing power but also with entire computing systems combining whole system’s perspective. In our case, we applied this model into real working environment and extend to HA cluster system at run time. In order to scale the voltage dynamically, the system must recognize unique voltage demands per HA cluster system within optimal operating point. This task can be done by using a sensing unit. A sensor unit is used for communication between the system and the external power supply.

III. RELATED WORKS Power management and monitoring scheme is increasingly recognized as an important challenge

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Figure 2: Power Supply Architecture

In our study we utilize adaptive voltage and current scaling method. Adaptive voltage scaling technique has been previously applied in many cases. However, we will simultaneously utilize current scaling method not for particular device component but in terms of entire system requirements. In most of the portable devices, AVS has been utilized which can save about 64% as compared to fixed-voltage supplying method. IV. WORKING PRINCIPAL In our system, we utilize adaptive voltage scaling technique with current scaling. In order to dynamically increase the voltage and current level, we have designed an array module that sense the load demands and this sensing unit will switch other power supply. Figure 1 shows the entire architectural design of our power supply. It has two power source that can take input of AC and DV voltage. This unit is connected with voltage regulator array unit. Voltage regulator unit is attached with voltage sensing unit. This sensing occurred at runtime. That means, our system provides power on demand basis. For example, in our cluster we have 10 nodes and while few nodes are on, then only a corresponding voltage regulator will be activated and supply the voltage. However, while further nodes are on, then the sensing unit will activate other voltage regulators in order to supply the additional energy. There is redundancy on voltage supply. If Ac mains is out the Devices gets power from battery. This feature is controlled by using a relay switch circuit. Voltage regulator arrays are responsible to supply the output voltage to HA cluster and other external devices connected to the system. Let’s assume an example that the load connected to voltage regulator goes on increasing, as loads goes on increasing the voltage regulator 1 will be unable to supply the demand which is required for load connected to it. Normally the connected device will not work, or regulator worn out, but this condition is remedied in this research. As soon as voltage regulator 1 cannot supply enough power to load connected, the sensing unit soon senses this situation and hence MCU gives control signal so that the voltage regulator 1 is soon

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Figure 3: Existing power supply adapter for HA cluster

supported by voltage regulator 2, if the supply is again insufficient voltage regulator 3 will come to support and so on. This system will hence provide continuous uninterrupted power supply to output devices. The new concept of borrowing power supply from other unit is implemented in this system. The similar power borrowing operation goes true for other voltage regulator 2, 3 and voltage regulator n units. In initial phase we are testing this research in 10 (n=10) voltage regulators. MCU (microcontroller unit) helps to controls the output voltage from linear voltage regulators. We have tested this by using an Arduino based program. Minicomputer unit is responsible to give the command and monitoring the overall operation of MCU unit and the voltage regulators online. V. CURRENT STATUS OF HA CLUSTER The main objective of this research is to find out and design the precise and effective power supply system for HA cluster shown in Figure 2. We will utilize this system in order to provide power supply to current HA cluster. Previous system is showing heating problems when two or more USB devices are connected to ports of Raspberry pi minicomputer. TABLE 1: POWER CONSUMPTION REPORT OF HA CLUSTER WITHOUT PERIPHERAL LOAD

Test No. 1 2 3 4 5 6 7 8 9 10

Ampere (Ac) 0.02 0.04 0.06 0.08 0.09 0.10 0.12 0.14 0.15 0.17


Power Consumed (W) 2.2 4.4 6.6 8.8 9.9 11 13.2 15.4 16.5 18.7

No of RPi. 1 2 3 4 5 6 7 8 9 10

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The system will be multipurpose and not only the HA cluster it will further support other external devices to. Above table shows the tested data which is performed in lab in Ac mains (110v system). It shows that as the number of RPi goes on increasing the demand of power is also linearly increasing. This test is done with RPi (Devian Wheezy OS) only and no any peripheral devices or load is connected to RPi. It shows that for n number of RPi we require a dynamic power supply system so that it can fulfil the instantaneous power requirement in HA cluster. That dynamic power supply system should have minimum losses and higher efficiency. Following tests and case studies were made in our lab in order to resolve above dynamic supply problem. VI. CASE STUDIES, DESIGN & DEVELOPMENTS In this study we test a normal 5V, 1A power supply system by feeding the output to RPi of Ha cluster. Figure 3 shows the power supply system we have utilized in this test. Following findings (Table 2 :) are obtained after this test in RPi used in HA Cluster TABLE 2: POWER CONSUMPTION REPORT BY USING EXISTING POWER ADAPTERS WITH PERIPHERAL LOAD

Test No.

No. of RPi

Average Power Consume d (Watt) 1.411 2.159 3.145

Condition of RPI Node

2 2 2

No.of Peripheral (WLI-UCGNM) 0 1 2

1 2 3

4 5

2 2

3 4

3.4 3.723

Freeze No Boot

working working Heating Problem

In above test we found that as the demand of power requirement keep on increasing, the current power supply system is unable to supply sufficient power required for HA Cluster. As shown in table 2, we utilize a minimum power consuming USB Wi-Fi dongle WLI-UC-GNM and make various test in order to obtain the data of power supply and power consumption. As number of WLI-UC-GNM increases excessive heating problem has been observed. Further this led to the operation of RPI to an unstable mode. In order to overcome this situation we should provide sufficient and uninterrupted power supply system. 1. Demand & Supply Analysis: As indicated in Table 2, it shows that the demand and supply is not matching and we observe various problem with RPi as load is simultaneously increased. The main issue behind such problem is due to power supply. We found that the demand of power is linearly increasing as the load is connected to RPi. The curve

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Figure 4：Demand VS Supply of Power

as shown in figure 4 indicates that load is increased from 0 to 4 number which were connected to USB ports. Note that, the demand curve is above than supply curve. There is a breakeven point at first RPi, however when RPi is increased, initially, both the demand and supply has been increased, nonetheless supply is not enough to meet the demand. A good adapter should be able supply enough power as soon as the demand increases while the loads are connected. Following figure shows the difference in demand and the supply with such existing power supply system. 2. Limitations of Existing USB Power Adapter: We found that existing USB adapter (figure 3) available in markets are limited to supply certain voltage levels (5.25 V) and are unable to supply sufficient current (1 A). Because of this limitation, HA cluster is not able to draw enough voltage and current required for its nodes. We can address this situation by using bigger adapter however which is not easily available and expensive in the market and also cannot supply power on demand to HA Cluster. Therefore, we design and developed an adaptive power management system after doing few empirical studies and simulations which are described in the sections below: A) Case Study 1: In order to address the limitation explained above, we make following design (figure 5) as our first initiation.

Figure 5: First Architecture used in Case Study 1


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Figure 9: Load VS Supply for First Prototype

Figure 6: First experiment (case study 1)

Figure 7: Voltage & Current output analysis for

Figure 10: Upgraded design (Case Study 2)

Figure 8: Prototype of first design A circuit was designed on the basis of this architecture which is shown in figure 6. The main components of this circuit is consisting of voltage regulator which operates within 1.25-37 V and within 1.5 A. On the basis of this device, we design a simulator and monitored the voltage and ampere operating ranges. Figure 7 shows the operating voltage and current ranges. However, note that this system may not work while the load exceeds the operating ranges. TABLE 3:

Test No.

No. of RPi

1. 2. 3. 4. 5.

1 1 1 1 1

No.of Peripheral (WLI-UCGNM) 0 1 2 3 4

Average Power Consume d (Watt) 1.422 2.209 3.910 5.221 6.123

Condition of RPI Node working working working working Heating Problem

The actual porotype design is depicted in figure 8. As load goes on increasing the voltage falls below the threshold and the connected device gets heating or restarting problem. Figure 7 shows the normal voltage and current outputs when a normal load is

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connected. Figure 9 shows the output result of device when 4 or more load (ie. RPi) are connected to USB. As shown in this graph, output voltage is dropped to 3.7V. This is under voltage situation which is not sufficient to drive the RPi that requires 5 V in order to operate without interruption. Therefore a more adaptive voltage regulator system is necessary that can address this situation. B)

Case Study 2 In case study two we changed our circuit and added an additional voltage regulator so that deficiency of voltage can be supplemented by using this additional regulator. The concept of this design is that by adding voltage regulators in parallel array we can modularize the architecture and also can provide the voltage demand as required by load. On the basis of this concept, we design a next model as shown in figure 10 which is consisted of two voltage regulators. These two regulators are designed such that whenever an additional voltage pull is occurred in a system, secondary voltage regulator gets ON to scale the voltage demand. In case study two, we have regulated output voltage by using LM117 voltage regulators with variable resistors. In order to scale the voltage dynamically, we need to further extend this design by adding computing devices. In following case study we use Arduino with transistors and other devices to control the operation of regulators which manage the voltage output as per the requirements dynamically.


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TABLE 4: ADAPTIVE VOLTAGE SCALING SIMULATION OUTPUT FOR HA CLUSTER

S. N

Load Condition

1.

No Load

2.

Load1 (Alone) Load2 (Alone) Load1 Load2 (Both)

3. 6.

Figure 11：Adaptive Voltage Scaling Architecture for HA Cluster

C)

Case Study 3 The empirical studies carried out in case study 1 & 2 were done without using any computing devices. This design generates some design flaw such as when the voltage and current output need to be adaptive, those designs cannot be applied. In a case, while voltage adaptation is required, a programmable supply system is necessary. In our final design, we consider this situation and test was done by using Arduino to control output according to the load. As shown in figure 11, a feedback voltage signal from output of each module is given to the analog input so that when voltage regulator1 cannot supply enough to load it will be then supported by regulator 2 and so on. The output voltage supplied to the load (Load1 to LoadN) is given as feedback signal to the analog input pin of Arduino, which further continuously monitors the output. If voltage level drops below the threshold level (say 5V) it automatically send signal to ON the voltage regulator2 via digital output pin as shown in the figure. And accordingly, it activates the further regulators connected in parallel. Circuit diagram as shown figure 11 clearly illustrates this explanation. In this simulation test we have taken N voltage regulators, and each regulator is equipped with NPN transistor. The task of this NPN transistor is to drive the voltage regulator according to the controlling signal received via Arduino computing device. In real scenario we are going to use 10 voltage regulators and implement this system to supply power to current HA Cluster. In next study we will study the feasibility of this dynamically controlled linear voltage regulator and then identify its benefits and shortcomings when dynamically controlled. In this way, we are able to adapt the voltage requirements of the system by activating corresponding voltage regulators.

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Output Voltag e (V) 5.27

Output Current (A) 0.000

5.27

1.024

5.27

1.024

5.27

2.045

Remarks

RG1 OFF RG 2 OFF RG 1 ON RG 2 OFF RG 1 OFF RG 2 ON RG 1 ON RG 2 ON

Table 4 shows the simulation data observed during our experiment. The notation of RG in remarks column means regulator which is used in our design. The remarks column Note that when the load is increased, it draws operating current from voltage regulator which is controlled automatically. In our first reading, there is no load and thus regulators are also in OFF status. After connecting the first load (Load1), Arduino sense the demand of voltage and current and hence turn on the voltage regulator 1 (RG1). In this way, the corresponding RG are turned on as per the load. VII. LIMITATIONS AND FUTURE WORKS As mentioned in the literature[9]–[12], most of the energy conservation is done by focusing on reducing the power consumption of CPU. However, CPU alone is not a dominating power consuming device for entire system as in HA cluster or in data centres. For example, computing systems have other power consuming units too such as memory, network interface cards, cooling fans, storage and other components which can significantly consume the power. Therefore, it is necessary to consider all sorts of computing components while minimize power consumption. In order to address this situation we applied hardware based dynamic voltage scaling method. This method is a straightforward method in which an external power management system make a power controlling decisions by monitoring their own utilization. The clear advantage of this method is that it does not provide excessive power nor it allows to operate on under rating. It just activates the corresponding voltage regulating device and power supply just to provide as demanded. On contrast, it has some limitations also. This scheme may perform poorly because it is unaware of the tasks or services running in the device or clusters. For example, in some situations cluster node may remain idle without delivering any services, however such situations cannot be detected in our hard ware based controlling system. Software-based DPM techniques [13], [14], [5], [15]can be applied to


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alleviate this problem. In our future work, we will utilize software-based DPM techniques in order to increase efficiency of our system which may require while implementing this method in more data intensive cloud centres. We have also not implemented the voltage and current monitoring system in our present design. This is remaining as our future works. We will use coulomb counting method to precisely measure the remaining charge of the voltage source (battery). This could be a crucial issue in order to guarantee a noninterruptible power supply. As described above, the ultimate goal of this research is to provide stable services even in disastrous situation, which is not possible without stable power supply. A more rigorous empirical study with workable prototype will be done in our next attempt. VIII. CONCLUSION The design of a power supply system on the basis of voltage adaptive method is architected and simulated which can sustain the peripheral load requirements. The design process should involve a very careful case studies and the analysis of load voltage and currents followed by a controlling program as described in this article. It is comparatively easy to design the system, once the loads have been pre-determined. The array of integrated circuits is presented in order to support these designs principals. On the basis of our case studies, the designer has the options of striving for maximum integration, minimum cost, and ease of use. In this research we proposed an auto voltage and current scaling scheme in order to properly manage the power supply for HA cluster. We believe that this architecture offers the efficiency improvements and savings not only during the design phase but also in operating costs that the cloud, cluster or any power consuming system need at run time. We applied this technique by designing and developing a power management system in real environment after having few simulation experiment and prototype design. We also demonstrated the architecture of our system so that power supply teams in the future can design more sophisticated and efficient power supply system. In this study a normal voltage regulator with output is tested and implemented. The output is first tested in simulator and then real hardware device is designed and tested in lab.

[4]

[5]

[6]

[7]

[8]

[9]

[10]

[11]

[12] [13] [14]

[15]

Management and Monitoring Approach March 2016 Bishnu Prasad Gautam,” Shuinshu University, 2016. B. P. Gautam, A. Batajoo, and K. Wasaki, “Fogging Jyaguchi Services in Tensai Gothalo (ITS研究会交通センシング,通信,情報処理,一般),” 電気学会研究会資料. Its, vol. 2015, no. 23, pp. 45–50, 2015. G. Chen, K. Huang, J. Huang, C. Buckl, and A. Knoll, “Effective online power management with adaptive interplay of DVS and DPM for embedded real-time system,” Proc. - 16th Euromicro Conf. Digit. Syst. Des. DSD 2013, pp. 881–889, 2013. D. R. Paudel, K. Sato, B. P. Gautam, and D. Shrestha, “Design and implementation of partial mesh community wireless network in Himalayan region,” Asian Himalayas Int. Conf. Internet, 2012. B. P. Gautam and K. Wasaki, “Deployment of Wi-Fi network as an emergency survival communication network in Wakkanai, Hokkaido,” IEEJ Trans. Electr. Electron. Eng., vol. 10, no. i, pp. S60–S68, 2015. D. R. Paudel, K. Sato, B. P. Gautam, and D. Shrestha, “Design and implementation of partial mesh community wireless network in Himalayan region,” 2012 Third Asian Himalayas Int. Conf. Internet, pp. 1–6, 2012. G. L. T. Chetsa, L. Lefevre, J. M. Pierson, P. Stolf, and G. Da Costa, “Beyond CPU frequency scaling for a finegrained energy control of HPC systems,” Proc. - Symp. Comput. Archit. High Perform. Comput., pp. 132–138, 2012. B. Khargharia, S. Hariri, F. Szidarovszky, M. Houri, H. El-Rewini, S. U. Khan, I. Ahmad, and M. S. Yousif, “Autonomic Power & Performance Management for Large-Scale Data Centers,” Ipdps, pp. 1–8, 2007. L. Mastroleon and N. Bambos, “Automatic power management schemes for Internet servers and data centers,” … 2005. Globecom’05 …, vol. 2, pp. 5–9, 2005. A. Musah and A. Dykstra, “OMAP35x Applications,” 2008. * K. M. A. and H. A. A. Mostafa A. El-Hosseini, “generate.pdf,” Ain Shams Eng. J., 2015. B. Brock and K. Rajamani, “Dynamic power management for embedded systems,” … . IEEE Int. [Systems-on-Chip], 2003. R. Cornea, N. Dutt, R. Gupta, S. Mohapatra, and A. Nicolau, “ServiceFORGE : A Software Architecture for Power and Quality Aware Services 2 . ServiceFORGE : A Software Architecture for Quality-Aware,” Architecture, 2008.

REFERENCES [1]

[2]

[3]

B. P. Gautam, K. Wasaki, and N. Sharma, “A Novel Approach of Fault Management and Restoration of Network Services in IoT Cluster to Ensure Disaster Readiness,” 2016. S. Shrestha, S. Kazuhiko, P. Shretha, and B. P. Gautam, “Multi-master Replication of an Enhanced Learning Assistant System in IoT Cluster,” pp. 1006–1012, 2016. B. P. Gautam, “Doctoral Dissertation ( Shinshu University ) Disaster Ready Networks : With a Novel

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