Resource Management and 3D Deployment in Power-Efficient Multi-UAV Networks

In this paper, the scenario in which multiple unmanned aerial vehicles (UAVs) provide service to ground users is considered. Under the condition of satisfying the minimum rate per user and system load balance, the user association, bandwidth allocation and three dimensional (3D) deployment of multi-UAV networks are optimized jointly to minimize the total downlink transmit power of UAVs. Since the problem is hard to solve directly, it is decomposed into three sub-problems, and then the problem is solved by alternating iteration algorithm. First, when the UAV’s location is determined, a modified K-means algorithm is used to obtain balanced user clustering. Then, when the user association and UAV’s 3D deployment are determined, the convex optimization method is used to obtain the optimal bandwidth allocation. Finally, when the user association and optimal bandwidth allocation are determined, a modified differential evolution algorithm is proposed to optimize the 3D location of the UAVs. Simulation results show that the proposed algorithm can effectively reduce the transmit power of UAVs compared with the existing algorithms under the conditions of satisfying the minimum rate of ground users and system load balance.

A price-aware congestion control protocol for cloud services

In current infrastructure-as-a service (IaaS) cloud services, customers are charged for the usage of computing/storage resources only, but not the network resource. The difficulty lies in the fact that it is nontrivial to allocate network resource to individual customers effectively, especially for short-lived flows, in terms of both performance and cost, due to highly dynamic environments by flows generated by all customers. To tackle this challenge, in this paper, we propose an end-to-end Price-Aware Congestion Control Protocol (PACCP) for cloud services. PACCP is a network utility maximization (NUM) based optimal congestion control protocol. It supports three different classes of services (CoSes), i.e., best effort service (BE), differentiated service (DS), and minimum rate guaranteed (MRG) service. In PACCP, the desired CoS or rate allocation for a given flow is enabled by properly setting a pair of control parameters, i.e., a minimum guaranteed rate and a utility weight, which in turn, determines the price paid by the user of the flow. Two pricing models, i.e., a coarse-grained VM-Based Pricing model (VBP) and a fine-grained Flow-Based Pricing model (FBP), are proposed. The optimality of PACCP is verified by both large scale simulation and small testbed implementation. The price-performance consistency of PACCP are evaluated using real datacenter workloads. The results demonstrate that PACCP provides minimum rate guarantee, high bandwidth utilization and fair rate allocation, commensurate with the pricing models.

Dynamic sampling from a discrete probability distribution with a known distribution of rates

In this paper, we consider several efficient data structures for the problem of sampling from a dynamically changing discrete probability distribution, where some prior information is known on the distribution of the rates, in particular the maximum and minimum rate, and where the number of possible outcomes N is large. We consider three basic data structures, the Acceptance–Rejection method, the Complete Binary Tree and the Alias method. These can be used as building blocks in a multi-level data structure, where at each of the levels, one of the basic data structures can be used, with the top level selecting a group of events, and the bottom level selecting an element from a group. Depending on assumptions on the distribution of the rates of outcomes, different combinations of the basic structures can be used. We prove that for particular data structures the expected time of sampling and update is constant when the rate distribution follows certain conditions. We show that for any distribution, combining a tree structure with the Acceptance–Rejection method, we have an expected time of sampling and update of $$O\left( \log \log {r_{max}}/{r_{min}}\right) $$ O log log r max / r min is possible, where $$r_{max}$$ r max is the maximum rate and $$r_{min}$$ r min the minimum rate. We also discuss an implementation of a Two Levels Acceptance–Rejection data structure, that allows expected constant time for sampling, and amortized constant time for updates, assuming that $$r_{max}$$ r max and $$r_{min}$$ r min are known and the number of events is sufficiently large. We also present an experimental verification, highlighting the limits given by the constraints of a real-life setting.

A Price-Aware Congestion Control Protocol for Cloud Services

In current infrastructure-as-a service (IaaS) cloud services, customers are charged for the usage of computing/storage resources only, but not the network resource. The difficulty lies in the fact that it is nontrivial to allocate network resource to individual customers effectively, especially for short-lived flows, in terms of both performance and cost, due to highly dynamic environments by flows generated by all customers. To tackle this challenge, in this paper, we propose an end-to-end Price-Aware Congestion Control Protocol (PACCP) for cloud services. PACCP is a network utility maximization (NUM) based optimal congestion control protocol. It supports three different classes of services (CoSes), i.e., best effort service (BE), differentiated service (DS), and minimum rate guaranteed (MRG) service. In PACCP, the desired CoS or rate allocation for a given flow is enabled by properly setting a pair of control parameters, i.e., a minimum guaranteed rate and a utility weight, which in turn, determines the price paid by the user of the flow. Two pricing models, i.e., a coarse-grained VM-Based Pricing model (VBP) and a fine-grained Flow-Based Pricing model (FBP), are proposed. The optimality of PACCP is verified by both large scale simulation and small testbed implementation. The price-performance consistency of PACCP are evaluated using real datacenter workloads. The results demonstrate that PACCP provides minimum rate guarantee, high bandwidth utilization and fair rate allocation, commensurate with the pricing models.

PENGARUH PERENCANAAN BIAYA TRANSPORTASI DALAM PENYUSUNAN ANGGARAN DAN PENGENDALIAN TERHADAP PENETAPAN EFISIENSI TARIF MINIMUM ANTARA GUDANG PENGIRIM DAN GUDANG PENERIMA PADA KEGIATAN ANGKUTAN REGIONAL BERAS DI DOLOG-JABAR

ABSTRAK Dennis Rydarto Tambunan: Penelitian ini bertujuan untuk mengetahui pengaruh perencanaan biaya transportasi dalam penyusunan anggaran dan pengendalian terhadap penetapan efisiensi tarif minimum antara gudang pengirim dan gudang penerima pada kegiatan angkutan regional beras di Dolog-Jabar. Perencanaan dalam penelitian ini meliputi perencanaan pengadaan persediaan beras, distribusi dan penyimpanan, catatan administrasi dan perhitungan. Selain itu, tujuan berikut adalah untuk mengetahui pengaruh perencanaan biaya transportasi terhadap sistem pengendalian intern persediaan, dan selanjutnya untuk mengetahui pengaruh sistem pengendalian intern persediaan (dalam hal ini sistem pengendalian intern persediaan adalah sebagai variabel penengah atau intervening variable) terhadap penetapan efisiensi tarif minimum. Efisiensi tarif minimum diukur agar dapat menjadi bahan pertimbangan bagi manajemen DOLOG-Jabar. Pengukuran efektivitas dan efisiensi dalam penelitian ini didasarkan pada pertimbangan antara anggaran biaya dengan realisasinya. Penggunaan realisasi ini dilakukan dengan menggunakan metode transportasi “Vogel Approximation Method”, untuk melihat seberapa besar efisiensi yang mungkin dicapai kalau metode ini diterapkan. Data dikumpulkan melalui studi dokumentasi serta membagikan kuesioner kepada kepala-kepala departemen dalam hal ini disebut manajer unit (Ka-Sie). Analisis data dilakukan dengan menggunakan analisis skor dan analisis jalur. Kuesioner yang digunakan didasarkan pada kuesioner yang dikembangkan oleh Roy A. Lindberg dan Theodore Chon, sedangkan struktur yang digunakan untuk analisis jalur didasarkan pada struktur yang dikembangkan oleh Ria R. Ariawati dan Harun Al Rasyid. Hasil penelitian menunjukkan bahwa perencanaan biaya transportasi dalam penganggaran secara bersama-sama berpengaruh positif terhadap sistem pengendalian intern persediaan dengan koefisien jalur sebagai berikut : PY1X1=0.001010712; PY1X2=0.095176407; PY1X3=0.511393824, dan koefisien determinasi (R2) sebesar R2 Y1(X1,X2,X3)=0,31722743 atau 31.72%. Sistem pengendalian intern persediaan berpengaruh positif terhadap efektivitas dan efisiensi penetapan tarif minimum dengan koefisien jalur sebagai berikut: PY2Y1 = RY2Y1 = 0.041907, dan koefisien determinasi (R2) adalah R2Y2(Y1)=0.0017562 atau 0.17562%. Adapun rata-rata efektivitas dan efisiensi yang dicapai Dolog-Jabar selama periode 1997-1998 yaitu 0.93 atau 93% ABSTRACT Dennis Rydarto Tambunan : The Influence Of Planning Transportation's Cost In The Making And Controlling Of The Budget Toward Fulfillment The Efficiency Of Minimum Rate Between Sender's Warehouse And Receiver's Warehouse On The Activity Of Rice's Regional Freight In DOLOG-Jabar, under advisorship of of Prof. Hj Ria Ratna Ariawati, and H. Moch. Mansur, SE, MM, Ak. This research aim is to understand the influence of planning transportation's cost in the making and controlling of the budget toward fulfillment the efficiency of minimum rate between sender's warehouse and receiver's warehouse on the activity :f rice's regional freight in DOLOG-Jabar. Planning in this research covers of preparing rice's stock, distribution and storage, administration and calculation. On the other hand, the other objection is to know the influence of planning transportation's cost toward internal control of inventory's system, and further more to know the influence of internal control of inventory's system (in this case internal control of inventory's system acts as an intervening variable) toward it's fulfillment on the efficiency of minimum rate. The efficiency of minimum rate was being measured so that it can be use as a judgement for the management of DOLOG-Jabar. The measurement in this research is based on the comparison between the budget and it's realization. The implementation of this realization was being done by making use of transportation method "Vogel Approximation Method", to see how large the efficiency might be achieved if this method applied. The research was done by using survey method in each department which act as units in DOLOG-Jabar located in Jln. Soekarno Hatta. The data was collected through the study of documentation as well as distributing questioners to every departmental heads in which is called as unit manager (Ka-Sie). Data analysis was done by using score and path analysis. The questioner used was based on the questioner developed by Roy A. Lindberg and Theodore Chon, while the structure used for the path analysis is based on the structure developed by Ria R. Ariawati and Harun Al-Rasyid. The result of this research shows that : Planning of transportation's cost in budgeting gives positive influence toward internal control of inventory's system with the path coefficient as follow: PY1X1=0.001010712; PY1X2=0.095176407; PY1X3=0.511393824, and the coefficient (R2) is R2 Y1(X1,X2,X3)=0,31722743 or 31.72%. Internal control of inventory's system gives positive influence toward it's effectiveness and it's efficiency in fulfillment minimum rate with path coefficient as follow PY2Y1 = RY2Y1 = 0.041907, and the coefficient determination (R2) is R2Y2(Y1)=0.0017562 or 0.17562%. The average effectiveness and efficiency that was achieved by DOLOG-Jabar during 1997-1998 was 0.93 or 93%. Keywords : Planning Transportation Cost; Budget Controlling; Efficiency Minimum Rate