Data aggregation, which is the process of summarizing a large amount of data, is an effective method for saving limited communication resources, such as radio frequency and sensor-node energy. Packet aggregation in wireless LAN and sensed-data aggregation in wireless sensor networks are typical examples. We propose and analyze two queueing models of fundamental statistical data aggregation schemes: constant interval and constant aggregation number. We represent each aggregation scheme by a tandem queueing network model with a gate at the aggregation process and a single server queue at a transmission process. We analytically derive the stationary distribution and Laplace-Stieltjes transform of the system time for each aggregation and transmission process and of the total system time. We then numerically evaluate the stationary mean system time characteristics and clarify that each model has an optimal aggregation parameter (i.e., an optimal aggregation interval or optimal aggregation number), that minimizes the mean total system time. In addition, we derive the explicit optimal aggregation parameter for a D/M/1 transmission model with each aggregation scheme and clarify that it provides accurate approximation of that of each aggregation model. The optimal aggregation interval was determined by the transmission rate alone, while the optimal aggregation number was determined by the arrival and transmission rates alone with explicitly derived proportional constants. These results can provide a theoretical basis and a guideline for designing aggregation devices, such as IoT gateways.

An approximation method for analyzing open queueing networks with nonpreemptive priority is presented. This method takes into account the variability of the arrival processes and service times for each node in the network, and hence a general class of non-Markovian models can be analyzed. The approximation procedure has following three steps: (1) the separation of the two-class priority network into two single-class networks, (2) the analysis of the flow rates and variability parameters of internal arrival processes for each class network, (3) calculation of traffic characteristics for each node in the single-class networks. For the first step, a two-parameter virtual server method is established, in which the arrival processes and service times are approximately characterized by the first and second moments. The second step is based on the decomposition method for single-class non-Markovian networks. At the third step, traffic characteristics for the entire networks are obtained by assuming that the nodes are independent. It is possible to quickly analyze large network models by this approach, because the procedure does not require iteration or a great amount of calculation. Numerical results are given and validated by exact and simulation results for a tandem network model and by simulatons for the basic component models of complex networks. Also, we apply our approximation method to an end-to-end delay analysis for a packet-switching network for voice and data. The results indicates that the accuracy of the approximation method is sufficient for practical use.

The spread of the Internet of Things (IoT) has led to the generation of large amounts of data, requiring massive communication, computing, and storage resources. Cloud computing plays an important role in realizing most IoT applications classified as massive machine type communication and cyber-physical control applications in vertical domains. To handle the increasing amount of IoT data, it is important to reduce the traffic concentrated in the cloud by distributing the computing and storage resources to the network edge side and to suppress the latency of the IoT applications. In this paper, we first present a recent literature review on fog/edge computing and data aggregation as representative traffic reduction technologies for efficiently utilizing communication, computing, and storage resources in IoT systems, and then focus on data aggregation control minimizing the latency in an IoT gateway. We then present a unified modeling for statistical and nonstatistical data aggregation and analyze its latency. We analytically derive the Laplace-Stieltjes transform and average of the stationary distribution of the latency and approximate the average latency; we subsequently apply it to an adaptive aggregation number control for the time-variant data arrival. The transient traffic characteristics, that is, the absorption of traffic fluctuations realizing a stable optimal latency, were clarified through a simulation with a time-variant Poisson input and non-Poisson inputs, such as a Beta input, which is a typical IoT traffic model.

In IEEE 802.11 wireless local area networks (WLANs), contention window (CW) in carrier sense multiple access with collision avoidance (CSMA/CA) is one of the most important techniques determining throughput performance. In this paper, we propose a novel CW control scheme to achieve high transmission efficiency in dense user environments. Whereas the standard CSMA/CA mechanism. Employs an adaptive CW control scheme that responds to the number of retransmissions, the proposed scheme uses the optimum CW size, which is shown to be a function of the number of terminal stations. In the proposed scheme, the number of terminal stations are estimated from the probability of packet collision measured at an access point (AP). The optimum CW size is then derived from a theoretical analysis based on a Markov chain model. We evaluate the performance of the proposed scheme with simulation experiments and show that it significantly improves the throughput performance.

In improving channel utilization in microcellular systems, adaptive channel allocation using distributed control has been reported to be effective. We describe an analytical approximation algorithm for channel dimensioning of distributed adaptive channel allocation. We compare our analytical results with simulation results and show the characteristics of permissible load as a function of the number of base station channels based on our method. Finally we illustrate traffic design and administration based on our algorithm.

When a link or node fails in a network, the affected flows are automatically rerouted. This increases the hop counts of the flows, which can drastically degrade network performance. Keeping the hop lengths as stable as possible, i.e., minimizing the difference in hop length between the original flow and the rerouted flow is important for network reliability. Therefore, network service providers need a method for designing networks that stabilizes the flow hop length and maintains connectivity during a link or node failure with limited investment cost. First, we formulate the network design problem used for determining the set of links to be added that satisfies the required constraints on flow hop length stability, connectivity, and node degree. Next, we prove that this problem is NP-complete and present two approximation algorithms for the optimization problem so as to minimize the number of links added. Evaluation of the performance of these algorithms by using 39 backbone networks of commercial ISPs and networks generated by two well-known models showed that the proposed algorithms provide effective solutions in sufficiently short computation time.

This paper proposes a novel access control scheme with collision detection that utilizes multiple-input multiple-output (MIMO) technology. Carrier sense multiple access with collision detection (CSMA/CD) is used in Ethernet wired local area networks (LANs) for media access control (MAC). CSMA/CD can immediately abort a transmission if any collision is detected and is thus able to change to a retransmission state. In Ethernet, CSMA/CD results in a transmission efficiency of approximately 90% because the protocol makes the transmission band available for useful communication by this retransmission function. Conversely, in conventional wireless LANs (WLANs), the packet collisions due to interfering signals and the retransmission due to collisions are significant issues. Because conventional WLANs cannot detect packet collisions during signal transmission, the success of a transmission can only be determined by whether an acknowledgment (ACK) frame has been received. Consequently, the transmission efficiency is low — approximately 60%. The objective of our study is to increase the transmission efficiency of WLANs to make it at least equal to that of Ethernet. Thus, we propose a novel access control scheme with collision detection that utilizes MIMO technology. When preamble signals are transmitted before transmitting data packets from an antenna, the proposed scheme can detect packet collisions during signal transmission at another antenna; then, the affected packets are retransmitted immediately. Two fundamental technologies are utilized to realize our proposed scheme. The first technology is the access control protocol in the MAC layer in the form of the MIMO frame sequence protocol, which is used to detect signal interference. The other technology is signal processing in the physical (PHY) layer that actualizes collision detection. This paper primarily deals with the proposed MAC layer scheme, which is evaluated by theoretical analyses and computer simulations. Evaluation by computer simulations indicate that the proposed scheme in a transmission efficiency of over 90%.

This paper presents busy/idle signal" scheme for control channel in mobile satellite communication systems. In the design of channel access schemes in mobile satellite communication systems, the following three factors must be taken into account: (1) a control channel is shared by call setup signals and response signals, (2) differences in propagation delays occur depending on the distance between the satellite and the mobile stations, (3) the number of retransmissions of a call setup signal is limited. Traffic performance measures of the proposed channel access scheme, such as throughput, mean setup delay and mean response delay, are compared with those of the random access scheme and the framed access scheme. A numerical method is presented for obtaining these measures, and the method's accuracy is demonstrated by comparing results with those obtained by simulation. This numerical method is very simple and is applicable to channel access schemes for mobile satellite communication systems with the above three factors. Using the numerical method, the proposed scheme is shown to be superior to other schemes.

An adaptive congestion control scheme that can be applied to various random access protocols in mobile communication systems is proposed. Its main features are scalability for handling increasing numbers of mobile terminals and adaptability for coping with drastic changes in traffic load. These are achieved by controlling the traffic load adaptively to maintain maximum throughput even under overload conditions. Procedure for measuring and estimating offered traffic and a method of setting control thresholds that maximize the average throughput are analytically derived, and the algorithm for adaptively controlling the permission rate is described. This scheme was applied to both the slotted ALOHA and ICMA/CD protocols. For each protocol, three control parameters--the unsuccessful rate, optimal traffic, and control thresholds--were analytically derived. Then stationary throughput characteristics were numerically evaluated. We found that the scheme could achieve high throughput by regulating transmission adaptively depending on the offered traffic. The preferred range of the permission base rate that enables adaptive control and limits the amount of processing at terminals was also clarified. Since one of the main advantages of our scheme is its adaptability to drastic variations in traffic load, we simulated its transient characteristics with three types of time-variant input models. The results indicate that this control scheme achieved nearly theoretically optimal throughput even during an overload for each input model.

Botnet threats, such as server attacks or sending of spam e-mail, have been increasing. Therefore, infected hosts must be found and their malicious activities mitigated. An effective method for finding infected hosts is to use a blacklist of domain names. When a bot receives attack commands from a Command and Control (C&C) server, it attempts to resolve domain names of C&C servers. We can thus detect infected hosts by finding these that send queries on black domain names. However, we cannot find all infected hosts because of the inaccuracy of blacklists. There are many black domain names, and the lifetimes of these domain names are short; therefore a blacklist cannot cover all black domain names. We thus present a method for finding unknown black domain names by using DNS query data and an existing blacklist of known black domain names. To achieve this, we focus on DNS queries sent by infected hosts. One bot sends several queries on black domain names due to C&C server redundancy. We use the co-occurrence relation of two different domain names to find unknown black domain names and extend the blacklist. If a domain name frequently co-occurs with a known black name, we assume that the domain name is also black. A cross-validation evaluation of the proposed method showed that 91.2% of domain names that are on the validation list scored in the top 1%.

Managing the performance at the flow level through traffic measurement is crucial for effective network management. With the rapid rise in link speeds, collecting all packets has become difficult, so packet sampling has been attracting attention as a scalable means of measuring flow statistics. In this paper, we firstly propose a method of estimating TCP flow rates of sampled flows through packet sampling, and then develop a method of detecting performance degradation at the TCP flow level from the estimated flow rates. In the method of estimating flow rates, we use sequence numbers of sampled packets, which make it possible to improve markedly the accuracy of estimating the flow rates of sampled flows. Using both an analytical model and measurement data, we show that this method gives accurate estimations. We also show that, by observing the estimated rates of sampled flows, we can detect TCP performance degradation. The method of detecting performance degradation is based on the following two findings: (i) sampled flows tend to have high flow-rates and (ii) when a link becomes congested, the performance of high-rate flows becomes degraded first. These characteristics indicate that sampled flows are sensitive to congestion, so we can detect performance degradation of flows that are sensitive to congestion by observing the rate of sampled flows. We also show the effectiveness of our method using measurement data.

A mobility management scheme that reduces signaling traffic load and connection setup time is a pivotal issue in designing future personal communication service (PCS) networks to satisfy Quality of Services requirements and use network resources efficiently. Particularly, required is scalable mobility management, to meet the explosive growth in number of users for the current second-generation wireless communication systems, and to materialize PCS concepts such as terminal, personal, and service mobility. Many mobility management schemes have been proposed for the reduction of signaling traffic. However, these schemes have not been sufficiently compared using a unified performance measure that is free of assumptions as to mobility model or database architecture. In this paper, we categorize the various mobility management schemes for advanced PCSs in distributed environments into four types and clarify the appropriate domain for each type. To do this, we settled on the number of signals at connection setup and location registration as a unified performance measure, since this value closely relates to connection setup time and network efficiency. We found two kinds of schemes with replicating and caching functions of user information that are extremely effective for reducing signaling load and hence connection setup time. These schemes are appropriate when the probability that a user is in his/her home area is relatively small or the connection setup rate is relatively high compared to the location registration rate. These are the most likely situations in the advanced PCS for global environments.

In this paper, we propose an access control protocol method that maintains the communication quality of various applications and reduces packet loss of multicasts in wireless local area networks. Multicast transmission may facilitate effective bandwidth use because packets are simultaneously delivered to more than one mobile station by a single transmission. However, because multicast transmissions does not have a retransmission function, communication quality deteriorates because of packet collisions and interference waves from other systems. Moreover, although multicasts are not considered, the communication quality of each application is guaranteed by a priority control method known as enhanced distributed channel access in IEEE802.11e. The proposed method avoids both these issues. Specifically, because the proposed method first transmits the clear-to-send-to-self frame, the multicast packet avoids collision with the unicast packet. We validate the proposed method by computer simulation in an environment with traffic congestion and interference waves. The results show a reduction in multicast packet loss of approximately 20% and a higher multicast throughput improvement compared to conventional methods. Moreover, the proposed method can assure improve multicast communication quality without affecting other applications.