| 1. |
- Adjiashvili, David, et al.
(författare)
-
Exact and Approximation Algorithms for Optimal Equipment Selection in Deploying In-Building Distributed Antenna Systems
- 2015
-
Ingår i: IEEE Transactions on Mobile Computing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1536-1233 .- 1558-0660. ; 14:4, s. 702-713
-
Tidskriftsartikel (refereegranskat)abstract
- We consider a combinatorial optimization problemin passive In-Building Distributed Antenna Systems (IB-DAS) deployment for indoor mobile broadband service. These systems have a tree topology, in which a central base station is connected to a number of antennas located at tree leaves via cables represented by the tree edges. Each inner node corresponds to a power equipment, of which the available types differ in the number of output ports and/or by power gain at the ports. This paper focuses on the equipment selection problemthat amounts to, for a given passive DAS tree topology, selecting a power equipment type for each inner node and assigning the outgoing edges of the node to the equipment ports. The performance metric is the power deviation at the antennas from the target values. We consider as objective function the minimization of either the total or the largest power deviation over all antennas. Our contributions are the development of exact pseudo-polynomial time algorithms and (additive) fully-polynomial time approximation schemes for both objectives. Numerical results are provided to illustrate the algorithms. We also extend some results to account for equipment cost.
|
|
| 2. |
- Biasson, A, et al.
(författare)
-
A decentralized optimization framework for energy harvesting devices
- 2018
-
Ingår i: IEEE Transactions on Mobile Computing. - 1536-1233 .- 1558-0660. ; 17:11, s. 2483-2496
-
Tidskriftsartikel (refereegranskat)abstract
- Designing decentralized policies for wireless communication networks is a crucial problem, which has only been partially solved in the literature so far. In this paper, we propose a Decentralized Markov Decision Process (Dec-MDP) framework to analyze a wireless sensor network with multiple users which access a common wireless channel. We consider devices with energy harvesting capabilities, that aim at balancing the energy arrivals with the data departures and with the probability of colliding with other nodes. Over time, an access point triggers a SYNC slot, wherein it recomputes the optimal transmission parameters of the whole network, and distributes this information. Every node receives its own policy, which specifies how it should access the channel in the future, and, thereafter, proceeds in a fully decentralized fashion, with no interactions with other entities in the network. We propose a multi-layer Markov model, where an external MDP manages the jumps between SYNC slots, and an internal Dec-MDP computes the optimal policy in the short term. We numerically show that, because of the harvesting, stationary policies are suboptimal in energy harvesting scenarios, and the optimal trade-off lies between an orthogonal and a random access system.
|
|
| 3. |
- Combes, Richard, et al.
(författare)
-
Optimal Rate Sampling in 802.11 Systems : Theory, Design, and Implementation
- 2019
-
Ingår i: IEEE Transactions on Mobile Computing. - : IEEE COMPUTER SOC. - 1536-1233 .- 1558-0660. ; 18:5, s. 1145-1158
-
Tidskriftsartikel (refereegranskat)abstract
- Rate Adaptation (RA) is a fundamental mechanism in 802.11 systems. It allows transmitters to adapt the coding and modulation scheme as well as the MIMO transmission mode to the radio channel conditions, to learn and track the (mode, rate) pair providing the highest throughput. The design of RA mechanisms has been mainly driven by heuristics. In contrast, we rigorously formulate RA as an online stochastic optimization problem. We solve this problem and present G-ORS (Graphical Optimal Rate Sampling), a family of provably optimal (mode, rate) pair adaptation algorithms. Our main result is that G-ORS outperforms state-of-the-art algorithms such as MiRA and Minstrel HT as demonstrated by experiments on a 802.11n network test-bed. The design of G-ORS is supported by a theoretical analysis, where we study its performance in stationary radio environments where the successful packet transmission probabilities at the various (mode, rate) pairs do not vary over time, and in non-stationary environments where these probabilities evolve. We show that under G-ORS, the throughput loss due to the need to explore sub-optimal (mode, rate) pairs does not depend on the number of available pairs. This is a crucial advantage as evolving 802.11 standards offer an increasingly large number of (mode, rate) pairs. We illustrate the superiority of G-ORS over state-of-the-art algorithms, using both trace-driven simulations and test-bed experiments.
|
|
| 4. |
- Eriksson, Emil, et al.
(författare)
-
Predictive Distributed Visual Analysis for Video in Wireless Sensor Networks
- 2016
-
Ingår i: IEEE Transactions on Mobile Computing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1536-1233 .- 1558-0660. ; 15:7, s. 1743-1756
-
Tidskriftsartikel (refereegranskat)abstract
- We consider the problem of performing distributed visual analysis for a video sequence in a visual sensor network that contains sensor nodes dedicated to processing. Visual analysis requires the detection and extraction of visual features from the images, and thus the time to complete the analysis depends on the number and on the spatial distribution of the features, both of which are unknown before performing the detection. In this paper, we formulate the minimization of the time needed to complete the distributed visual analysis for a video sequence subject to a mean average precision requirement as a stochastic optimization problem. We propose a solution based on two composite predictors that reconstruct randomly missing data, on quantile-based linear approximation of feature distribution and on time series analysis methods. The composite predictors allow us to compute an approximate optimal solution through linear programming. We use two surveillance video traces to evaluate the proposed algorithms, and show that prediction is essential for minimizing the completion time, even if the wireless channel conditions vary and introduce significant randomness. The results show that the last value predictor together with regular quantile-based distribution approximation provide a low complexity solution with very good performance.
|
|
| 5. |
- He, Qing, et al.
(författare)
-
Maximum Link Activation with Cooperative Transmission and Interference Cancellation in Wireless Networks
- 2017
-
Ingår i: IEEE Transactions on Mobile Computing. - : IEEE. - 1536-1233 .- 1558-0660. ; 16:2, s. 408-421
-
Tidskriftsartikel (refereegranskat)abstract
- We address the maximum link activation problem in wireless networks with new features, namely when the transmitters can perform cooperative transmission, and the receivers are able to perform successive interference cancellation. In this new problem setting, which transmitters should transmit and to whom, as well as the optimal cancellation patterns at the receivers, are strongly intertwined. We present contributions along three lines. First, we provide a thorough tractability analysis, proving the NP-hardness as well as identifying tractable cases. Second, for benchmarking purposes, we deploy integer linear programming for achieving global optimum using off-theshelf optimization methods. Third, to overcome the scalability issue of integer programming, we design a sub-optimal but efficient optimization algorithm for the problem in its general form, by embedding maximum-weighted bipartite matching into local search. Numerical results are presented for performance evaluation, to validate the benefit of cooperative transmission and interference cancellation for maximum link activation and to demonstrate the effectiveness of the proposed algorithm.
|
|
| 6. |
- Jang, Insun, et al.
(författare)
-
A Proxy-Based Collaboration System to Minimize Content Download Time and Energy Consumption
- 2017
-
Ingår i: IEEE Transactions on Mobile Computing. - : IEEE Computer Society. - 1536-1233 .- 1558-0660. ; 16:8, s. 2105-2117
-
Tidskriftsartikel (refereegranskat)abstract
- Mobile collaborative community (MCC) is an emerging technology that allows multiple mobile nodes (MNs) to perform a resource intensive task, such as large content download, in a cooperative manner. In this paper, we introduce a proxy-based collaboration system for the MCC where a content proxy (CProxy) determines the amount of chunks and the sharing order scheduled to each MN, and the received chunks are shared among MNs via Wi-Fi Direct. We formulate a multi-objective optimization problem to minimize both the collaborative content download time and the energy consumption in an MCC, and propose a heuristic algorithm for solving the optimization problem. Extensive simulations are carried out to evaluate the effects of the number of MNs, the wireless bandwidth, the content size, and dynamic channel conditions on the content download time and the energy consumption. Our results demonstrate that the proposed algorithm can achieve near-optimal performance and significantly reduce the content download time and has an energy consumption comparable to that of other algorithms.
|
|
| 7. |
- Josilo, Sladana, et al.
(författare)
-
Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks
- 2019
-
Ingår i: IEEE Transactions on Mobile Computing. - : IEEE COMPUTER SOC. - 1536-1233 .- 1558-0660. ; 18:1, s. 207-220
-
Tidskriftsartikel (refereegranskat)abstract
- Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper, we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices, we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.
|
|
| 8. |
- Kouyoumdjieva, Sylvia T., et al.
(författare)
-
Impact of Duty Cycling on Opportunistic Communication
- 2016
-
Ingår i: IEEE Transactions on Mobile Computing. - 1536-1233 .- 1558-0660. ; 15:7, s. 1686-1698
-
Tidskriftsartikel (refereegranskat)abstract
- A major challenge in mobile wireless devices for opportunistic networks is to decrease the energy consumption. The decrease should not come at a cost of reduced application throughput (i.e. goodput). This work evaluates the potential performance gains for mobile nodes that adopt duty cycling in an opportunistic context. The paper presents an analytical framework for evaluating goodput and energy consumption of nodes based on a probabilistic estimation of effective contact durations, and it validates this framework on a mobility scenario. The study shows that both goodput and energy consumption depend strongly on the distribution of listening durations, and that goodput is independent of the contact rate among nodes. This work also includes extensive trace-driven simulations and demonstrates that duty cycling considerably improves the performance of opportunistic networks by decreasing the energy consumption without significantly affecting the goodput.
|
|
| 9. |
- Lau, Chun Pong, et al.
(författare)
-
An Efficient Content Delivery System for 5G CRAN Employing Realistic man Mobility
- 2019
-
Ingår i: IEEE Transactions on Mobile Computing. - : IEEE COMPUTER SOC. - 1536-1233 .- 1558-0660. ; 18:4, s. 742-756
-
Tidskriftsartikel (refereegranskat)abstract
- Today's modern communication technologies such as cloud radio access and software defined networks are key candidate technologies for enabling 5G networks as they incorporate intelligence for data-driven networks. Traditional content caching in the last mile access point has shown a reduction in the core network traffic. However, the radio access network still does not fully leverage such solution. Transmitting duplicate copies of contents to mobile users consumes valuable radio spectrum resources and unnecessary base station energy. To overcome these challenges, we propose huManmObility-based cOntent Distribution (MOOD) system. MOOD exploits urban scale users' mobility to allocate radio resources spatially and temporally for content delivery. Our approach uses the broadcast nature of wireless communication to reduce the number of duplicated transmissions of contents in the radio access network for conserving radio resources and energy. Furthermore, a human activity model is presented and statistically analyzed for simulating people daily routines. The proposed approach is evaluated via simulations and compared with a generic broadcast strategy in an actual existing deployment of base stations as well as a smaller cells environment, which is a trending deployment strategy in future 5G networks. MOOD achieves 15.2 and 25.4 percent of performance improvement in the actual and small-cell deployment, respectively.
|
|
| 10. |
- Lee, Kyunghan, et al.
(författare)
-
Max Contribution : An Online Approximation of Optimal Resource Allocation in Delay Tolerant Networks
- 2015
-
Ingår i: IEEE Transactions on Mobile Computing. - 1536-1233 .- 1558-0660. ; 14:3, s. 592-605
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, a joint optimization of link scheduling, routing and replication for delay-tolerant networks (DTNs) has been studied. The optimization problems for resource allocation in DTNs are typically solved using dynamic programming which requires knowledge of future events such as meeting schedules and durations. This paper defines a new notion of approximation to the optimality for DTNs, called snapshot approximation where nodes are not clairvoyant, i.e., not looking ahead into future events, and thus decisions are made using only contemporarily available knowledges. Unfortunately, the snapshot approximation still requires solving an NP-hard problem of maximum weighted independent set (MWIS) and a global knowledge of who currently owns a copy and what their delivery probabilities are. This paper proposes an algorithm, Max-Contribution (MC) that approximates MWIS problem with a greedy method and its distributed online approximation algorithm, Distributed Max-Contribution (DMC) that performs scheduling, routing and replication based only on locally and contemporarily available information. Through extensive simulations based on real GPS traces tracking over 4,000 taxies and 500 taxies for about 30 days and 25 days in two different large cities, DMC is verified to perform closely to MC and outperform existing heuristically engineered resource allocation algorithms for DTNs.
|
|
