WWW Server Load Balancing Technique Employing Passive Measurement of Server Performance 59
WWW Server Load Balancing Technique
Employing Passive Measurement of Server
Satoru Ohta1 and Ryuichi Andou2 , Non-members
ABSTRACT • The speciﬁcations of the servers are not necessarily
Server load balancing is indispensable within identical; servers with diﬀerent capacities may coex-
World Wide Web (WWW) for providing high-quality ist.
• The server load incurred by a request is not con-
service. In server load balancing, since the server
loads and capacities are not always identical, traf- stant. Some requests may oﬀer much heavier load
ﬁc should be distributed by measuring server perfor- than others.
mance to improve the service quality. This study pro- Because of these characteristics, the performance
poses a load balancing technique conducted by pas- of some servers is relatively degraded. Thus, the
sive measurement, which estimates the server per- server load may become imbalanced if requests are
formance via user traﬃc passing through the load distributed to each server with equal probability.
balancer. Since this method evaluates server perfor- The above problem is avoided by measuring the
mance without executing any programs on the server, performance of each server and distributing fewer re-
no additional server or network load is generated. quests to servers that do not have suﬃcient capac-
This paper ﬁrst presents a server performance metric ities. Such control has been achieved by executing
that can be passively measured. The presented met- a load/performance measurement program on each
ric utilizes the characteristics of TCP SYN and SYN machine and by transmitting the measurement result
ACK messages exchanged in the TCP connection es- to the load balancer [1, 2]. The load balancer can
tablishment phase. An experiment shows that the then distribute requests to server considering their
metric correctly identiﬁes server performance degra- load/performance. However, by executing the mea-
dation. The paper then proposes a load balancing surement program on the servers, this method may
algorithm based on the metric, and its implementa- generate additional processing loads on them. More-
tion issues. The proposed algorithm distributes fewer over, if a servers performance is extremely degraded
requests to servers that do not have suﬃcient capac- with excessive loads, the program may not function
ities. Because of this, the algorithm achieves good eﬃciently.
performance in a heterogeneous environment where As an alternative method, this study investigates
servers with diﬀerent capacities coexist. The eﬀec- the passive measurement approach, in which server
tiveness of the proposed load balancing technique is performance is estimated via the user traﬃc passing
conﬁrmed experimentally. through the load balancer. Since this approach does
not generate any additional loads on the servers or
Keywords: IP Networks, Load Balancing, WWW, the network, the estimation is not aﬀected by mea-
TCP, Passive Measurement, Performance surement program/packets. Passive measurement ap-
proaches have been reported in [3, 4]. However, the
1. INTRODUCTION method proposed in the present study is more ad-
The World Wide Web (WWW) is the most impor- vantageous because its performance metric is ob-
tant service provided by the Internet. The quality tainable by simpler computation. The Linux Vir-
of the service depends on the capacity of the servers; tual Server [5, 6] and NetDispatcher  are also load
if service demand exceeds the capacity of a server, balancing methods based on passive measurement.
multiple servers are employed to share the load, and These methods distribute load among servers by es-
achieve an acceptable service quality [1, 2]. timating the number of TCP connections. However,
The following characteristic must be considered in the number of TCP connections does not necessar-
order to establish a powerful load balancing tech- ily represent the server performance and thus is not
nique. an appropriate metric for load balancing in a hetero-
geneous environment. By contrast, the metric pre-
Manuscript received on August 1, 2009 ; revised on November sented in this paper correctly identiﬁes server perfor-
5, 2009. mance. Because of this, the proposed method is more
1,2 The authors are with the Department of Information
eﬀective when some servers are more degraded than
Systems Engineering, Faculty of Engineerig, Toyama Prefec-
tural University, 5180 Kurokawa, Imizu-shi, Toyama, 939-0398,
Japan., Email: firstname.lastname@example.org The proposed measurement method uses the fact
60 ECTI TRANSACTIONS ON ELECTRICAL ENG., ELECTRONICS, AND COMMUNICATIONS VOL.8, NO.1 February 2010
that server performance degradation is identiﬁed method, the program itself generates additional pro-
through the packets exchanged in the establishment cessing load on the server, deteriorating its perfor-
phase of a TCP connection. Based on this idea, this mance. Moreover, if a server’s performance is ex-
paper presents a new server performance metric that tremely degraded with excessive load, the measure-
can be measured passively, and subsequently applies ment program may not work eﬃciently. Thus, any
the performance metric to load balancing. The paper method based on a measurement program executed
describes the algorithm that controls the probabilities on the server is not reliable.
of distributing requests according to the performance An alternative regarding server load/performance
metric. The eﬀectiveness of the proposed metric and estimation is to measure the response time of the
the load balancing technique is conﬁrmed experimen- ICMP echo message. However, this response time
tally. does not always represent the load or performance of
The proposed load-balancing technique is applica- the server accurately. Moreover, the ICMP messages
ble to any TCP server-client based services. However, oﬀer additional traﬃc to the network and the servers,
since WWW is the most heavily used service in the aﬀecting system performance.
Internet, the load-balancing for WWW is more fre- As seen above, existing techniques have disadvan-
quently required. Therefore, this paper focuses on tages relating to additional loads or inaccuracy. To
WWW as the application of the proposed method. establish an ideal load balancing method, the server
The paper ﬁrst overviews related studies and de- load/performance must be estimated through passive
scribes the problem tackled in this study in Sect. 2. measurement, monitoring only the user traﬃc. This
Section 3 presents a server performance metric, es- approach does not insert any probe packets into the
timated through passive measurement. This section network or execute any programs on the server ma-
shows that the metric is closely related to the TCP chines.
connection time. Section 4 details the proposed load
Load balancing techniques based on passive mea-
balancing technique. Finally, Sect. 5 concludes the
surement have been examined in [3, 4]. For the
performance metric, the method of  employs the
application-layer round-trip time, while the method
2. RELATED WORKS AND PROBLEM DE- of  employs the ﬂow rate. For the estimation of
SCRIPTION these metrics, the variables used for the computation
So that the load balancer maximizes system per- must be managed individually for each TCP connec-
formance, service requests should not be distributed tion. Since a server handles many TCP connections,
to all servers with equal probability . This is be- the estimation of the metrics requires a large amount
cause WWW services often involve complex process- of storage and computational time. Thus, it is nec-
ing, and the load induced by the processing varies essary to establish a performance metric that is pas-
greatly with the content of a request. As a result, sively measured and estimated by a simpler process
the load on each server is not always the same even than the methods of [3, 4]. In addition, these meth-
if every server receives the same number of service ods have been evaluated only by computer simula-
requests. Further, the capacities of servers are not tions and have not been implemented on real net-
always identical. For example, suppose that the ser- works. Thus, their feasibility is unclear.
vice demand has increased, and the current number Implemented load balancing techniques include
of servers is insuﬃcient for handling requests. In this the Linux Virtual Servers [5, 6] and NetDispacher .
case, new server machines must be added to the sys- The former uses the number of current TCP connec-
tem, and it is very likely that the capacities of the tions as the server load metric while the latter uses
newly purchased machines are larger than those of the number of TCP connections as well as server ma-
the old machines. Moreover, the performance of a chine information gathered by agent programs. In
server may degrade comparatively because of faults these techniques, the number of TCP connection is
such as RAID disk trouble. passively measured. However, the number of TCP
To solve the above problem, we measure the perfor- connections is not directly related to the server ca-
mance of each server and distribute service requests pacity or performance. Obviously, a high-capacity
based on this performance, reﬂecting the remaining server machine can accept many concurrent connec-
capacity of the machine. More requests need to be tions while a low-capacity machine can accept fewer
distributed to a server with greater remaining ca- connections. Meanwhile, the techniques consider that
pacity and fewer requests to a server with less re- a machine with fewer connections is lightly loaded.
maining capacity. Therefore, advanced load balanc- Thus, the techniques route a new connection to the
ing techniques employ a mechanism, to estimate the machine that has the fewest connections. This oper-
load/performance of servers. ation minimizes the diﬀerence among the number of
Existing load balancing techniques often employ TCP connections handled by each machine. There-
a program running on each server to measure its fore, the techniques will oﬀer a similar number of
load/performance [2, 8]. Unfortunately, with this TCP connections to a high-capacity machine as that
WWW Server Load Balancing Technique Employing Passive Measurement of Server Performance 61
to a low-capacity machine. It would therefore ap- a large amount of storage and computational time.
pear that this operation is not adequate for the case Meanwhile, the approach of this study manages only
in a heterogeneous environment. For load balancing the numbers of TCP SYN and SYN ACK packets
in heterogeneous environments, it is necessary to de- and does not manage each connection. Therefore, its
velop a metric that reﬂects server performance and computational procedure is much simpler than that
can be passively measured. of the method of Ref. .
Several studies have indicated that the perfor- The numbers of TCP SYN and SYN ACK mes-
mance of a WWW server is closely related to the sages can be measured passively and represent server
socket accept queue [9–11]. If excessive load is oﬀered performance degradation. This characteristic is well
to a server, the socket accept queue buﬀer overﬂows suited to load balancing in heterogeneous environ-
with TCP SYN messages, and if the message is lost, ments. The following sections describe how this is
the client retransmits the TCP SYN message after achieved.
the timeout period. This timeout and retransmission
process greatly increases the connection time. Thus, 3. SERVER PERFORMANCE METRIC
if the accept queue overﬂow is identiﬁed from the user
traﬃc, excessive server load and performance degra- 3. 1 Theory
dation can be detected eﬀectively. An important aspect of server performance is
By utilizing the above characteristics, Refs. [9, 10] the connection time, which is deﬁned as the period
examine server capacity estimation based on TCP needed to set up a TCP connection. The connec-
SYN drop rate for the purpose of energy conserva- tion time depends on several factors, such as packet
tion. In , the ratio of SYN ACK messages and communication delay in the network or processing de-
TCP SYN messages is used to detect SYN ﬂood De- lay at the server. However, it is reported that the
nial of Services (DoS) attack. However, the above- most dominant factor aﬀecting connection time is the
mentioned characteristics of TCP SYN and SYN buﬀer overﬂow of the socket accept queue [9, 11]. The
ACK messages have not been investigated from the retransmission process for a lost TCP SYN message
viewpoint of server load balancing. takes a few seconds, while the other delays are shorter
The technique reported in Reference  utilizes than one second. Thus, other delays are almost neg-
TCP SYN/SYN ACK messages in a diﬀerent way ligible in comparison with those caused by TCP SYN
to distribute load among multiple access links. The retransmission.
technique passively measures round trip times by Let t0 be the timeout period for the TCP SYN re-
recording arrival times of TCP SYN and SYN ACK transmission. We assume that the ﬁrst TCP SYN is
messages. Load is then distributed among access lost, and the retransmitted second TCP SYN estab-
links according to the measured round trip times. To lishes the TCP connection successfully. Thus, the
execute this method, the arrival times of TCP SYN connection time is greater than t0 . Similarly, the
and SYN ACK messages must be managed individ- lower bound of the connection time is nt0 for n re-
ually for each TCP connections. Therefore, if many transmissions of a TCP SYN message. Moreover, the
TCP connections are set up in the network, the tech- connection time can be approximated by nt0 assum-
nique will require a large amount of processing load ing that other delays are much smaller than t0 .
and storage. By contrast, the approach of this study If a TCP SYN is accepted, the server sends back a
does not need to manage each connection and thus is SYN ACK message to the client. Thus, the number
achieved with much less processing load and storage of retransmitted TCP SYN messages is estimated by
A diﬀerent aspect of load-balancing is found in counting the number of TCP SYN messages transmit-
Ref. , which reports on a content switch. The con- ted before receiving a SYN ACK message. If NA TCP
tent switch distributes load according to the contents connections are established for a speciﬁed period, the
of service requests and not according to server per- server generates NA SYN ACK messages. Let NS be
formances. Therefore, the method of Ref.  is not the number of TCP SYN messages sent to the server
necessarily eﬀective for heterogeneous environment, for that period. The number of overﬂow TCP SYN
which is the target of this study. From the view- messages is then approximated by NS − NA . The
point of TCP SYN/SYN ACK message utilization, average number of the retransmitted TCP SYN mes-
the method of Ref.  ﬁnds a pre-allocate server sages for a connection is thus (NS − NA )/NA . This
from the source IP address shown in a TCP SYN implies that the average connection time tc is approx-
packet to reduce the processing load of converting se- imated by the following equation.
quence numbers. The method also uses the sequence
numbers indicated in TCP SYN/SYN ACK messages (NS − NA )t0
for converting the sequence numbers. To perform tc ≈ . (1)
this, the IP addresses and the sequence numbers must
be managed individually for each TCP connection. The above equation suggests that the following
For this reason, the method of Ref.  consumes value R is an eﬀective metric for server performance.
62 ECTI TRANSACTIONS ON ELECTRICAL ENG., ELECTRONICS, AND COMMUNICATIONS VOL.8, NO.1 February 2010
Measurement: Metric R 600 0.2
WWW Client WWW Server
Average Connection Time (msec)
Proposed Performance Metric, R
500 Proposed Metric, R
PC2 Page Data PC1 PC0
Fig.1: Network conﬁguration to evaluate the perfor- 100
mance metric R.
0 200 400 600 800 1000
Connection Request Rate (requests/sec)
NS − NA
R= . (2)
Fig.2: Relationship between the proposed perfor-
It is clear from eq.(1) that the value R is propor- mance metric R and the average TCP connection
tional to the average connection time. Therefore, the time.
degradation of server performance can be evaluated
with increase of R.
The beneﬁts of employing R from eq.(2) are sum- tion time and the metric R. The ﬁgure shows that
marized as follows. the characteristics of R almost exactly coincide with
• The parameters that are used to compute R, are those of the connection time. Therefore, we can em-
obtained through passive measurement of user traf- ploy R rather than measuring the connection time,
ﬁc. This means that the metric R can be estimated whose estimation is more diﬃcult. It is also observed
without oﬀering an additional load on the server or that performance degradation is identiﬁed correctly
the network. through the proposed metric R.
• The metric R can be easily computed and can be Figure 2 shows that the average connection time
obtained without managing TCP connections. Thus, is nearly 3000 times R. Thus, the above character-
the amount of computational time and storage is istics and eq.( 2) imply that the timeout period of
much smaller for this metric than for the metrics used TCP SYN retransmission is about 3 seconds in the
in previous works such as [3, 4, 13, 14]. experimental environment. This result agrees com-
pletely with the initial timeout speciﬁed in Sect. 4.2.3
3. 2 Evaluation of Ref. . This conﬁrms that the metric R is de-
termined by the mechanism described in Sect. 3.1 of
To show the eﬀectiveness of the proposed metric
the present paper.
R, an experiment was executed. The experiment em-
ployed three Linux PCs (PC0, PC1, and PC2) con- In the Fig. 2, small diﬀerences between R and the
nected by 1 Gb/s Ethernet, as shown in Fig. 1. The connection time appear at certain points. These dif-
PCs used in the experiment are 3.06 GHz Celeron ferences are caused by delay factors other than TCP
machines with Plamo Linux 4.1, Kernel 184.108.40.206. A SYN retransmission.
WWW server (Apache) runs on PC0, while the client
runs on PC2. The client program (httperf ) gen- 4. LOAD BALANCING TECHNIQUE
erates HTTP GET requests for 1 × 105 byte ﬁles on This section describes a load balancing technique
the WWW server. The interval between requests is in which the load balancer estimates the performance
randomly determined according to the exponential metric R for each server. If R is greater for one server
distribution. The connection time was measured by than for others, the load balancer judges that machine
the client program, and the proposed metric R was to have a lower remaining capacity. Thus, the load
measured on PC1. The obtained connection time and balancer decreases the machine traﬃc. Details of the
metric R were compared. The proposed metric R was load control algorithm and some implementation is-
measured using tcpdump . That is, tcpdump was sues are described below.
executed on PC1 during the measurement period to
capture every packet whose SYN ﬂag was set. By
4. 1 Algorithm
recording TCP SYN and SYN ACK packets in this
manner, the numbers of TCP SYN and SYN ACK Suppose that n servers, 1, 2, . . . , n, oﬀer the same
messages, NS and NA , were counted. Then, the met- services and share requests from the clients. Let ri
ric R was computed by eq.(2). (0 ≤ ri ≤ 1) be the traﬃc ratio for server i (1 ≤
The result is shown in Fig. 2. The x-axis is the i ≤ n), i.e., (traﬃc given to server i)/(total traﬃc).
traﬃc load represented by the TCP connection re- Moreover, assume the environment to be heteroge-
quest rate, whereas the y-axis is the average connec- neous, and the capacities of some servers to be rela-
WWW Server Load Balancing Technique Employing Passive Measurement of Server Performance 63
tively greater. Thus, it is necessary to feed diﬀerent Number of SYNs/ACKs for t [90, 100) s3 a3
traﬃc loads to each server so as to maximize the total Number of SYNs/ACKs for t [80, 90) s2 a2
performance. Number of SYNs/ACKs for t [110, current time] s1 a1
A greater value of the metric R means that the Number of SYNs/ACKs for t [100, 110) s0 a0
machine has less remaining capacity and that its per-
formance is degraded. Thus, the average connection Ns sk N A ak
time will be improved by decreasing the load from k 0 k 0
such a machine. The actions of the algorithm are as
follows: Fig.3: Counter conﬁguration for calculating the
1. Measure the numbers of TCP SYN and SYN ACK metric R every 10 seconds from data obtained in a
messages for each server periodically, and compute 40-second period.
the metric R.
2. Select the server that has the largest value of R
among servers 1, 2, . . . , n. Let j denote the selected
sk − ak
3. Decrease the traﬃc ratio rj by δ (0 < δ < rj ),
while increasing ri (i = j) by δ/(n − 1). R= m−1
4. 2 Implementation
Simultaneously, sk and ak , which hold the oldest data
To implement the proposed algorithm, some issues
among the counters, are reset to zero. This procedure
must be addressed. The ﬁrst is the manner in which
is illustrated by Fig. 3.
the TCP SYN and SYN ACK messages are counted
The size of the time window, mT , must be suf-
during an appropriate time period. If the numbers
ﬁciently large to obtain a reliable value of R. If the
of TCP SYN and SYN ACK messages are estimated
time-window size is too small, very few lost TCP SYN
for a too long period of time, it becomes impossible
messages are counted during the time window. For
to control traﬃc adequately against a rapid change
such a case, it is diﬃcult to obtain an adequate num-
of server performance. Thus, the counted number of
ber of samples for reliable estimation of R.
these messages must be updated smoothly to reﬂect
the changes in server performance against time. To The second issue is how the parameter δ should
achieve such an update, this study examines the fol- be chosen in the algorithm. Since the traﬃc ratio rj
lowing scheme. cannot be less than 0, δ should not exceed rj . Thus,
this study examines the value
Assume that the metric R is computed every T
seconds from the numbers of TCP SYN and SYN
ACK messages, arriving during the most recent mT δ = ∆rj (0 < ∆ < 1). (6)
seconds (m: integer). This means that R is computed
The value of ∆ must be much smaller than 1. To
from TCP SYN and SYN ACK messages that have
understand this, let us suppose that the load is now
arrived in the time window whose size is mT seconds.
shared among two server machines denoted by S0 and
Let s0 , s1 , . . . , sm−1 be m counters to count TCP SYN
S1 and that the value of ∆ is close to 1, for example,
messages, while a0 , a1 , . . . , am−1 are m counters to
0.99. Additionally, consider that the metric R for S0
count SYN ACK messages. In addition, let t denote
becomes larger than that for S1 . Then, the algorithm
the current time in seconds. Counter sk (or ak ) is
routes most of the traﬃc load to S1 . Since this de-
incremented by 1 for each TCP SYN (or SYN ACK)
grades the performance of S1 , R will become larger
message arriving during the period,
for S1 than for S0 . Thus, at the next control event,
most of traﬃc load will be routed to S0 . This means
(N m + k)T ≤ t < (N m + k + 1)T, (3) that the loads on S0 and S1 oscillate with the period
of the control event interval. Needless to say, such
where N is an integer. For example, if T is 10 seconds, oscillation is undesirable and thus must be avoided
s0 is incremented for 0 ≤ t < 10, s1 is incremented by setting ∆ to a suﬃciently small value.
for 10 ≤ t < 20, and so on. Then, when the current Meanwhile, a small ∆ will slow down the response
time satisﬁes of the control against performance changes because
the load will change very slightly at each control
event. Although further study is needed to ﬁnd an
t = (N m + k)T, (4) optimal value of the parameter ∆, the experimental
result suggests that ∆ = 0.1 is a good setting.
for integer k, the metric R for the most recent mT It is easy to distribute requests to server i accord-
seconds is computed by ing to ri , by employing the iptables command of the
64 ECTI TRANSACTIONS ON ELECTRICAL ENG., ELECTRONICS, AND COMMUNICATIONS VOL.8, NO.1 February 2010
Server PCs (Apache) 900
Equal Load among Servers
Average Connection Time (msec)
Hard Disk Proposed Method
Client PC Load Balancer PC & I/O Load 700
(httperf) (Proposed Method)
Lightly Loaded 300
Fig.4: Network conﬁguration evaluating the pro- 100 200 300 400 500
posed load balancing method. Connection Request Rate (requests/sec)
Fig.5: The average connection time versus the con-
Linux OS. The iptables command supports Desti-
nection request rate for the proposed method and the
nation Network Address Translation (DNAT) suited
equal load case.
to load balancing . Moreover, the load for each
server can be controlled using the “statistic” exten-
sion and its “probability” option . Thus, the load tions generated by httperf. This measurement was
is exactly divided among each server by calculating repeated 15 times for each connection request rate,
the probability given to the iptables rule from ri . and then the average connection time was obtained.
The initial value of ri was 1/3 for every server PC.
4. 3 Evaluation The parameters ∆, m, and T , used in the proposed
The eﬀectiveness of the presented load balancing method (see Sect. 4.2), were set at 0.1, 10, and 20, re-
technique was evaluated through an experiment per- spectively. This means that the traﬃc ratio for each
formed on the network as shown in Fig. 4. The server is updated every 10 seconds on the basis of
network is conﬁgured with three server PCs, a load TCP SYN and SYN ACK messages counted for the
balancer PC, and a client PC. These PCs are con- most recent 200 seconds. In addition, the traﬃc for
nected by two local networks (1 Gb/s Ethernet). The the most deteriorated server is decreased by 10 %
Apache WWW server was running on the server PCs, when the traﬃc ratio is updated. The value of ∆
while httperf was executed on the client PC to gen- was set suﬃciently small to avoid load oscillation as
erate HTTP GET requests and measure the perfor- described in Sect. 4.2. The time-window size, 200
mance. The proposed technique was executed on the seconds, was chosen to obtain an adequate number of
load balancer PC for distributing the requests to the lost TCP SYN messages for reliable estimation.
server PCs. The technique was implemented as a C In the experiment, the PCs for the client, the
language program that utilizes the pcap library  load balancer and the heavily loaded server are 3.06
to capture TCP SYN and SYN ACK packets from GHz Celeron machines. Meanwhile, the PCs for the
user traﬃc. When the program receives a TCP SYN lightly loaded servers are 1.60 GHz Celeron machines.
(or SYN ACK) packet, it updates the counter sk (or Although the hardware speciﬁcation of the heavily
ak ) as described in Sect. 4.2. Meanwhile, it computes loaded server is superior to that of the lightly loaded
the metric R every T seconds and modiﬁes the traﬃc server, its performance is worse because of the artiﬁ-
ratios r1 , r2 , . . . , rn by executing the iptables com- cial load oﬀered by stress. The OS employed in the
mand. PCs is Plamo Linux 4.1, Kernel 220.127.116.11.
The experiment was performed for a situation in Figure 5 shows the average connection time against
which server performances diﬀer greatly. This situ- the connection request rate. Evidently, the connec-
ation is generated by running a stress tool  on tion time is shorter for the proposed method than for
one server PC and generating excessive hard disk and the equal-load case. This result is obtained because
I/O load. By executing httperf on the client PC, the proposed method eﬀectively reduces the traﬃc for
HTTP GET requests are issued for a 1 × 105 byte the server degraded by a heavy load.
HTML ﬁle on the servers in a random interval de- Figure 6 depicts the changes in traﬃc ratio ri as-
termined according to the exponential distribution. signed to the server PCs against time. The ﬁgure
The average connection time for this setting was mea- shows that the load on the degraded PC eﬀectively
sured by httperf, for the case applying the proposed decreases with time. This means that most requests
method as well as for the case in which the traﬃc are sent to the server PCs with a light load, and thus
was distributed to servers with equal probability. The do not suﬀer from serious connection delay. In addi-
connection time was measured for 105 TCP connec- tion, the performance of the degraded server is also
WWW Server Load Balancing Technique Employing Passive Measurement of Server Performance 65
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66 ECTI TRANSACTIONS ON ELECTRICAL ENG., ELECTRONICS, AND COMMUNICATIONS VOL.8, NO.1 February 2010
Satoru Ohta received the B.E., M.E.,
and Dr. Eng. degrees from the Tokyo
Institute of Technology, Tokyo, Japan,
in 1981, 1983, and 1996, respectively. In
1983, he joined NTT, where he worked
on research and development of cross-
connect systems, broadband ISDN, net-
work management, and telecommunica-
tion network planning. Since 2006, he
has been a professor with the Depart-
ment of Information Systems Engineer-
ing, Faculty of Engineering, Toyama Prefectural University,
Imizu, Japan. His curret research interests are performance
management of information networks and network protocols.
He is a member of the IEEE and IEICE. He received the Ex-
cellent Paper Award in 1991 from IEICE.
Ryuichi Andou recieved the B.E. de-
gree from Toyama Prefectural Univer-
sity, Imizu, Japan, in 2008. He is
now a master course student in the De-
partment of Information Systems Engi-
neering, Faculty of Engineering, Toyama
Prefectural University. His research in-
terests are network monitoring and net-