ASUS EEPC horror story

Last week I was at the Tridentcom conference in Innsbruck. There, while attending a talk, I saw first-hand the horror of a presentation gone completely wrong, the discomfort of the audience, and the pain of an embarrassed speaker as his ASUS EEPC failed miserably. The presenters beautiful slides were cut horizontally (about 30% of the lower part of each slide was missing) because the ASUS EEPC could not drive the overhead projector properly. Every other laptop, including old clunky student-budget ones, running Windows , Linux, and Mac OS, were successful in beaming presentations. But not the ASUS EEPC.

There are many objective reviews of laptops on the Internet based on specifications, design, speed, etc. They try to compare products side by side so that potential buyers can choose the product that is best for them. Still, somethings are considered standard and not even mentioned - like the assurance that the power adaptor will charge the laptop's battery, the battery won't burst, the USB ports will work, and the VGA output will work. Seasoned customers are smart enough to get a mix of online and off-line opinions about a product before buying it. But sometimes when products are just released, it is hard to ascertain whether a product will serve its purpose down the road. I hope this EEPC horror story gives folks some additional information before they buy it.

Its all nice to tout the small, cheap ASUS EEPC. But seriously, didn't VGA-out technology mature like 15 years ago? And ASUS cannot even get this right in 2008? My 2 cents - get a second or third hand Pentium 3 laptop or something instead.

Recursion and "Towers of Hanoi"

Figure 1: rules of the Hanoi puzzle. Click to enlarge

I was thinking of my first algorithms class and remembered the "Towers of Hanoi" problem. This problem is used to introduce the concept of recursion. It can also use the stack data structure (LIFO) quite naturally, making it a universal favorite in assignments. An Internet search yields 1000's of websites discussing the problem. Heres adding yet another discussion to this timeless classic!

Problem Setup
Here is the setup and the rules of the Hanoi puzzle

1. There are 3 towers labeled 0,1, and 2.
2. There are N circular discs, each of different radius, that are initially placed around tower 0.
3. Any circular disc can only be placed above a disc of larger radius, or as the first disc of the tower.

The objective is to move the N discs from tower 0 to tower 2 following the rules mentioned above.

Figure 1 explains the problem graphically and shows the rules of the Hanoi puzzle.

Solution
In order to solve the puzzle recursively, look at Figure 2. The first requirement on moving the largest (red) disc from tower 0 (source tower) to tower 2 (destination tower) is that there should be no discs over this red disc. This means that the other 2 discs (green and yellow) should be moved to tower 1 (auxiliary tower) and the setup should be in state 1. Then, the red disc can be moved to tower 2 (state 2).

Now the problem is reduced to one with just 2 discs (yellow and green). These need to be moved from tower 1 (the source) to tower 3 (the destination) using tower 0 as a temporary go-between (auxiliary tower).

Figure 2: Top level steps. Click to enlarge

But wait, how do we accomplish the transition from state 0 to state 1?
Figure 3 shows the intermediate steps to accomplish this. The aim is to move the green and yellow discs from tower 0 (source) to tower 1 (destination) using tower 2 as the auxiliary tower.

Figure 3: Mini-steps from state 0 to state 1. Click to Enlarge

So the high-level idea is to have a function that recursively places the discs in the appropriate towers. This will be clear in the C++ "Hanoi" function shown below. I have used STL data-structures (vector and stack) in order to simplify the explanation.

#include <stack>
#include <vector>

#include <iostream>

using namespace std;

//Each Tower is a Stack (LIFO)
vector <stack <int>*> towers; //Vector of pointers to stacks

//Printing the tower contents. This is only for eye-candy.

void PrintTowers()
{
stack <int> tempStack;
for (int ii=0;ii<towers.size();ii++) {

 cout << std::endl<< "Tower " << ii <<": ";
 while (!towers[ii]->empty()) {

  tempStack.push(towers[ii]->top());
  towers[ii]->pop();
 }

 while (!tempStack.empty()) {
  towers[ii]->push(tempStack.top());

  cout <<tempStack.top()<<"  "; 
  tempStack.pop();
 }
 cout << " <-- TOP";
}
}

//Move from Tower "from" to Tower "to"
void MoveDisc(int from, int to)
{
towers[to]->push(towers[from]->top());

towers[from]->pop();
}

//Recursive function Hanoi - the most interesting function
//When this function exits, it has moved the lowest
//Tower (as specified by numDiscs) from the sourceTower to the
//destTower using the auxTower as a temporary holder
void Hanoi(int sourceTower, int destTower, int auxTower, int numDiscs)
{

if (numDiscs==0)
 return;
Hanoi(sourceTower, auxTower, destTower, numDiscs-1);

MoveDisc(sourceTower,destTower);
Hanoi(auxTower,destTower,sourceTower,numDiscs-1);
}

int main()
{
int numDiscs;

cout << "Please enter the number of discs: ";

cin >> numDiscs;

//Initialize the Towers by allocating 3 stacks
 for (int ii=0;ii < 3;ii++)

 towers.push_back(new stack<int>);

//Initial condition: all the discs are on Tower 0
 for (int jj=numDiscs-1;jj >=0 ;jj--)

 towers[0]->push(jj);

//Print setup of towers
 cout <<std::endl<<"Initially";

PrintTowers();

//Enter recursive function here
 Hanoi(0, 2, 1, numDiscs);

//Print setup of towers
 cout <<std::endl<<"Finally";
PrintTowers();

//Don't forget to delete the vector of stacks.

 for (int ii=0;ii < 3; ii++)

 delete towers[ii];

cout << std::endl << "Done.";


return 0;
}

Our world needs electricity, lots of it.

(Click to enlarge)

I visited the UN data website and downloaded data about the total electricity production of countries and matched it with their populations in order to obtain the electricity produced per 1000 inhabitants (for each country). I have plotted a histogram of this in the figure above.

This histogram is disturbing.

The smaller issue is that inhabitants of most countries have lesser electricity than the world average. This means that a few energy-rich countries are producing (and probably consuming) most of the world's electricity. I have marked some of the representative countries on the histogram. There is a table at the end of this post containing the parsed data in case you want to look up your own country and/or use the data (After citing the UN data source, off course).

The bigger issue is that countries with low electricity per capita (bars toward the left of the figure) are striving to move the per capita electricity production higher to improve quality of life. For example, both India and China are lower than the world average. And I have the impression that these countries are really looking to improve their citizen's living conditions. And remember, populations are increasing too (see one of my previous posts), making it necessary to pump up electricity production even faster.

Producing more electricity is a positive development. But the problems associated with increasing production are the issue here. Here are some questions:

1. Where are we going to get the energy to increase electricity production so rapidly?
2. What will be the environmental cost of creating so much additional capacity? I hope it is renewable energy. Hope. Hope. Hope.
3. Or, does this analysis indicate that even in the next decades electricity will be a premium, for-the-well-off, limited quantity luxury given the lack of such a massive energy source?

Tough cookies.

We really need a breakthrough with some new technology here.



Here is the table containing data used in the analysis.
Country, million kWh per 1000 inhabitants (German notation: "," is the decimal point)

Afghanistan	0,019507403
Albania	0,529214445
Algeria	0,219150336
American Samoa	0,936753525
Angola	0,032618392
Anguilla	1,036227154
Antigua and Barbuda	0,325148424
Argentina	0,727408376
Armenia	1,07765584
Aruba	1,457768448
Australia	2,492244294
Austria	2,280999506
Azerbaijan	0,617455344
Bahamas	1,40738335
Bahrain	2,551090802
Bangladesh	0,027811644
Barbados	0,739895798
Belarus	0,819169464
Belgium	1,54779036
Belize	0,174199589
Benin	0,006949106
Bermuda	2,726961075
Bhutan	0,549439336
Bolivia	0,149749265
Bosnia and Herzegovina	0,69957433
Botswana	0,118195712
Brazil	0,49861704
British Virgin Islands	0,454215116
Brunei Darussalam	2,030329213
Bulgaria	1,545853099
Burkina Faso	0,005598074
Burundi	0,004199119
Cambodia	0,013614697
Cameroon	0,049170704
Canada	3,765512578
Cape Verde	0,157851016
Cayman Islands	2,346954443
Central African Republic	0,010259031
Chad	0,002858379
Chile	0,798215316
China	0,386906459
Colombia	0,296546128
Comoros	0,006266434
Congo	0,025762836
Cook Islands	0,57208238
Costa Rica	0,44965969
Croatia	0,849392177
Cuba	0,379683488
Cyprus	1,34517727
Czech Republic	1,708438639
Democratic People's Republic of Korea	0,402276274
Democratic Republic of the Congo	0,043802793
Denmark	2,471503772
Djibouti	0,146728575
Dominica	0,353841391
Dominican Republic	0,582812306
Ecuador	0,273103278
Egypt	0,280151791
El Salvador	0,184723191
Equatorial Guinea	0,026854067
Eritrea	0,036892038
Estonia	1,702729723
Faeroe Islands	1,804792034
Falkland Islands (Malvinas)	3,025210084
Fiji	0,199264292
Finland	3,139151247
French Guiana	0,728790884
French Polynesia	0,442041685
Gabon	0,325406584
Gambia	0,018552543
Georgia	0,977777798
Germany	1,51273341
Ghana	0,065320583
Gibraltar	1,202749141
Greece	1,20759618
Greenland	1,844280122
Grenada	0,304075563
Guadeloupe	0,937493585
Guam	3,274604022
Guatemala	0,162208554
Guinea	0,022771058
Guinea-Bissau	0,01315024
Guyana	0,415837246
Haiti	0,023772922
Honduras	0,212566084
Hungary	0,856203515
Iceland	5,200654647
India	0,126738013
Indonesia	0,116874477
Iran (Islamic Republic of)	0,639435492
Iraq	0,300043035
Ireland	1,518598487
Israel	1,541832479
Jamaica	0,425354403
Japan	2,168335174
Jordan	0,389966498
Kazakhstan	1,231640364
Kenya	0,034242581
Kiribati	0,032607632
Kuwait	4,02037037
Kyrgyzstan	0,710476911
Lao People's Democratic Republic	0,08121598
Latvia	0,940571111
Lebanon	0,601385281
Liberia	0,054622645
Libyan Arab Jamahiriya	0,865970274
Lithuania	1,330189073
Luxembourg	3,631083653
Madagascar	0,012230063
Malawi	0,01376068
Malaysia	0,829451232
Maldives	0,165934635
Mali	0,0098182
Malta	2,28753381
Marshall Islands	0,303244006
Martinique	1,000262695
Mauritania	0,058047217
Mauritius	0,554314346
Mexico	0,490100396
Mongolia	0,322392649
Montserrat	1,776830135
Morocco	0,172225006
Mozambique	0,115377076
Myanmar	0,024954518
Namibia	0,034659007
Nauru	0,989021857
Nepal	0,022551405
Netherlands	1,3307455
Netherlands Antilles	1,126657796
New Caledonia	1,528705938
New Zealand	2,168356638
Nicaragua	0,099770455
Niger	0,007916051
Nigeria	0,041604152
Niue	0,612745098
Oman	1,189848435
Pakistan	0,123101766
Palau	2,583594177
Panama	0,508432302
Papua New Guinea	0,117468448
Paraguay	1,25604174
Peru	0,228699463
Philippines	0,185003073
Poland	0,844522287
Portugal	1,269159686
Puerto Rico	1,370991383
Qatar	3,553189833
Republic of Korea	1,389956686
Romania	0,876196974
Russian Federation	1,619416414
Rwanda	0,004223616
Saint Helena	0,625097672
Saint Kitts and Nevis	0,407016973
Saint Lucia	0,40932771
Saint Pierre and Miquelon	4,254648598
Saint Vincent and the Grenadines	0,29377943
Samoa	0,157741576
Sao Tome and Principe	0,032760677
Saudi Arabia	1,420230761
Senegal	0,048341849
Seychelles	1,110695412
Sierra Leone	0,008771297
Singapore	2,347562131
Slovakia	1,624096551
Slovenia	1,496430224
Solomon Islands	0,02963471
South Africa	0,835171394
Spain	1,888334973
Sri Lanka	0,126093294
Sudan	0,030204543
Suriname	0,859729307
Swaziland	0,122718045
Sweden	3,694381387
Syrian Arab Republic	0,398277093
Tajikistan	0,678298553
Thailand	0,52931205
The former Yugoslav Republic of Macedonia	0,767583489
Timor-Leste	0,042163059
Togo	0,007694068
Tonga	0,080514488
Trinidad and Tobago	1,118059532
Tunisia	0,326482221
Turkey	0,532316671
Turkmenistan	0,811252681
Turks and Caicos Islands	0,163538984
Uganda	0,010743706
Ukraine	1,119794335
United Arab Emirates	3,827701301
United Kingdom	1,358755508
United Republic of Tanzania	0,01426794
United States of America	3,558514712
Uruguay	0,629035396
Uzbekistan	0,440301803
Vanuatu	0,055719101
Viet Nam	0,140517355
Western Sahara	0,131690083
Zambia	0,196892977
Zimbabwe	0,178739129

GENI and Networking Research: Inside out, or outside in?

The Global Environment for Network Innovations (GENI) idea is to build an experimental facility that researchers can use to experiment with new communications and networking technology, distributed systems, cyber-security aspects, and applications. A couple of weeks ago I attended a talk given by Craig Patridge, chief scientist at BBN technologies. Craig is heading the GENI project office tasked with implementing GENI. He is an engaging speaker and got me thinking about the merits of building GENI.


GENI is a sort of first for the National Science Foundation (NSF) and the network research community. NSF occasionally funds large infrastructure projects like building astronomy telescopes and particle accelerators but this is the first time that a networking infrastructure is being funded. The interesting thing is that the infrastructure comes first and then protocols or services follow. Moreover, the infrastructure will be built based on requirements specified by the research community. Is this the future of network research?


The current Internet is an engineering marvel. It scaling property is absolutely remarkable - 100s of millions of hosts in a federated environment with completely different underlying access technologies just work. Then the creative engineers and innovators come in to shape the Internet APIs (e.g. IP communication stack) into myriad applications - email, VOIP, P2P, Web 2.0, digital libraries, and whatever else they can think of.


The Internet was first built by engineers, and later scientists highlighted several flaws in its design. This has sometimes served as a good feedback loop for refining the Internet over time. For example, security researchers have continually unearthed security holes in the IP socket stack. Scientists, coming from the outside, study the insides of the Internet and contribute to refining the already-built Internet.


But can researchers with limited engineering experience design a new communication infrastructure such as the GENI infrastructure? I very much doubt this. Researchers are seldom successful in building viable commercial technologies. They are very smart but usually focused on one or few problems. It is not at all clear if GENI could deliver the next Internet.

But lets back-pedal a little. Is GENI supposed to be building the next Internet? Answer: perhaps not. But what I find troubling about the GENI (or FIRE - the European counterpart) is that there is that almost the whole OSI stack - network, transport, session and applications - is supposed to come from the research community. I really really wonder who is going to write all this up? Off course there can be a module-based approach to plugging in pre-existing pieces into GENI, but then how is this Internet design revolutionary, and does this justify building GENI in the first place? Why not stick with something more real like PlanetLab?


I don't believe scientists can build another Internet from the inside out. Shouldn't building a new network, from the inside, be left to the engineers?

Bullish about mobile/cellular networks

(Click to enlarge. Source: UN data)

We all know that cellular mobile networks are rapidly expanding all over the world - in fact the rate of adoption of cellular mobile technology has been faster than that of the Internet. I am bullish about this technology's role in human development. The bar-graph says it all. Amen!

The Internet gets a heavy tail

(Click to enlarge)

The above plot shows the growth of the Internet in the World, again from UN data. There are 3 histograms (2004, 2001, 1998) of the number of countries (Y axis) vs. the size of the Internet population in the countries (X axis). I have left out the countries with less than 1m users because they are the vast majority in the data - partly due to low Internet adoption in backward areas and partly due to small populations.

The key points seen immediately

1. The number of Internet users is (surprise surprise) growing rapidly over the years.
2. USA leads every other country, but since the total US population is only about 300m (see my previous post), US Internet users' growth is saturating.
3. On the other hand, China is growing very quickly. I suppose by 2008 (present) the number of users there must have got close to the US number (if not ahead).

But lets look at a more holistic trend here. This is the "long fat tail" that shows up in the 2004 data - the bars concentrated on the left hand side have started spreading out to the right in the 2004 histogram. This means that the Internet is increasingly becoming multinational with a significant representation of people from many countries, bringing up these questions

1. Where is the Internet content suitable for people from different cultures and not just western cultures?
2. Are we doing enough to localize Internet applications for these large multicultural groups joining the Internet?

Finally, for those interested, here is a table showing the number of Internet users, as reported by the most recent data from UN Statistics (2004). I have ranked the countries based on the number of Internet users in the rightmost columns of the table. Again, if you look at the top 10 countries in this table, only 2 have a high number of English native speakers. In addition, 5 out of the top 10 countries are not "Northern hemisphere western countries".

Please use this data only after citing the UN source.

Country	#Internet users	Rank (2004)
United States	185000000	1
China	94000000	2
Japan	64160000	3
United Kingdom	37600000	4
Germany	35200000	5
India	35000000	6
Korea, Republic of	31580000	7
Italy	28870000	8
France	25000000	9
Brazil	22000000	10
Canada	20000000	11
Russian Federation	16000000	12
Indonesia	14508000	13
Spain	14332800	14
Mexico	14036500	15
Australia	13000000	16
Turkey	10220000	17
Netherlands	10000000	18
Malaysia	9879000	19
Poland	9000000	20
Thailand	6972000	21
Sweden	6800000	22
Argentina	6153600	23
Viet Nam	5870000	24
Iran (Islamic Republic of)	5500000	25
Czech Republic	5100000	26
Romania	4500000	27
Philippines	4400000	28
Chile	4300000	29
Belgium	4200000	30
Colombia	4050240	31
Austria	3900000	32
Egypt	3900000	33
Ukraine	3750000	34
South Africa	3566000	35
Morocco	3500000	36
Switzerland	3500000	37
China, Hong Kong Special Administrative Region	3479700	38
Finland	3286000	39
Peru	3220000	40
Israel	3200000	41
Portugal	2951000	42
Denmark	2725000	43
Hungary	2700000	44
Belarus	2461090	45
Singapore	2421780	46
Venezuela	2312680	47
Slovakia	2276060	48
New Zealand	2110000	49
Pakistan	2000000	50
Greece	1955000	51
Norway	1792000	52
Nigeria	1769660	53
Saudi Arabia	1586000	54
Serbia and Montenegro	1517020	55
Kenya	1500000	56
United Arab Emirates	1384840	57
Croatia	1303000	58
Bulgaria	1234000	59
Ireland	1198000	60
Sudan	1140000	61
Jamaica	1067000	62
Costa Rica	1000000	63
Lithuania	968000	64
Slovenia	950000	65
Uzbekistan	880000	66
Puerto Rico	862000	67
Tunisia	835000	68
Zimbabwe	820000	69
Latvia	810000	70
Dominican Republic	800000	71
Syrian Arab Republic	800000	72
Guatemala	756000	73
Uruguay	680000	74
Estonia	670000	75
Ecuador	624579	76
Jordan	600000	77
Kuwait	600000	78
Lebanon	600000	79
El Salvador	587475	80
Algeria	500000	81
Haiti	500000	82
Senegal	482000	83
Azerbaijan	408000	84
Republic of Moldova	406000	85
Kazakhstan	400000	86
Ghana	368000	87
Bolivia	350000	88
United Republic of Tanzania	333000	89
Malta	301000	90
Bangladesh	300000	91
Panama	300000	92
Cyprus	298000	93
Sri Lanka	280000	94
Luxembourg	270810	95
Kyrgyzstan	263000	96
Oman	245000	97
Cote d'Ivoire	240000	98
Zambia	231000	99
Iceland	225610	100
Bosnia and Herzegovina	225000	101
Honduras	222273	102
Togo	221000	103
Libyan Arab Jamahiriya	205000	104
Mongolia	200000	105
Reunion	200000	106
Uganda	200000	107
Mauritius	180000	108
Yemen	180000	109
Georgia	175600	110
Angola	172000	111
Papua New Guinea	170000	112
Cameroon	167000	113
Qatar	165000	114
Occupied Palestinian Territory	160000	115
Trinidad and Tobago	160000	116
The former Yugoslav Republic of Macedonia	159000	117
Bahrain	152721	118
Armenia	150000	119
Barbados	150000	120
China, Macao Special Administrative Region	150000	121
Cuba	150000	122
Paraguay	150000	123
Guyana	145000	124
Mozambique	138000	125
Nicaragua	125000	126
Nepal	120000	127
Ethiopia	113000	128
Martinique	107000	129
Benin	100000	130
Bahamas	93000	131
Madagascar	90000	132
Guadeloupe	79000	133
Guam	79000	134
Namibia	75000	135
New Caledonia	70000	136
Myanmar	63688	137
Fiji	61000	138
Botswana	60000	139
Brunei Darussalam	56000	140
Saint Lucia	55000	141
Burkina Faso	53200	142
Democratic Republic of the Congo	50000	143
Eritrea	50000	144
Mali	50000	145
Gambia	49000	146
Malawi	46140	147
Guinea	46000	148
French Polynesia	45000	149
Lesotho	43000	150
Cambodia	41000	151
Gabon	40000	152
Bermuda	39000	153
French Guiana	38000	154
Greenland	38000	155
Rwanda	38000	156
Congo	36000	157
Iraq	36000	158
Swaziland	36000	159
Turkmenistan	36000	160
Belize	35000	161
Chad	35000	162
Faeroe Islands	32000	163
Suriname	30000	164
United States Virgin Islands	30000	165
Guinea-Bissau	26000	166
Burundi	25000	167
Cape Verde	25000	168
Aruba	24000	169
Niger	24000	170
Liechtenstein	22000	171
Lao People's Democratic Republic	20900	172
Dominica	20500	173
Antigua and Barbuda	20000	174
Bhutan	20000	175
Sao Tome and Principe	20000	176
Seychelles	20000	177
Grenada	19000	178
Maldives	19000	179
San Marino	15000	180
Somalia	15000	181
Mauritania	14000	182
Micronesia, Federated States of	12000	183
Andorra	11000	184
Saint Kitts and Nevis	10000	185
Sierra Leone	10000	186
Central African Republic	9000	187
Djibouti	9000	188
Comoros	8000	189
Saint Vincent and the Grenadines	8000	190
Vanuatu	7500	191
Gibraltar	6295	192
Samoa	6000	193
Equatorial Guinea	5000	194
Tajikistan	5000	195
Palau	4000	196
Solomon Islands	3000	197
Tonga	3000	198
Tuvalu	3000	199
Kiribati	2000	200
Marshall Islands	2000	201
Netherlands Antilles	2000	202
Cayman Islands	1300	203
Liberia	1000	204
Nauru	300	205
Korea, Democratic People's Republic of	0	206